Author Archives: Hussain Fakhruddin

AI-as-a-Service: All That You Need To Know

 

AI services: Overview

In 2008, the worldwide software-as-a-service market was worth only $5.6 billion. Cut to 2020, and that figure is expected to soar to $133 billion – clearly indicating the rapid rise in demand for consumption-based software services (‘a la carte software’, so to speak). Between 2018 and 2020, the total number of SaaS subscriptions are set to jump by nearly 96%. This is, without a shadow of a doubt, one of the fastest growing technology sub-domains at present.

While services like Platform-as-a-Service (PaaS) and Infrastructure-as-a-Service (IaaS) have been in discussion for some time now – the ‘as-a-service’ market is gradually being extended into newer, more cutting-edge, fields. The artificial intelligence-as-a-service (AIaaS) market is a classic example of that. According to estimates, the worldwide AIaaS market will be valued at just a shade under $11 billion by the end of 2023, with the 2017-2023 CAGR hovering around the 49% mark. The biggest of players, like Microsoft, Google, IBM and Amazon, are already heavily active in this field. In today’s discussion, we will take a look at some interesting facets of the growth of AIaaS:

  1. What exactly is AIaaS?

    As the name itself suggests, AIaaS refers to off-the-shelf artificial intelligence service offerings that can be bought and implemented immediately. In other words, it can be explained as ‘third party AI service offerings’ as well. Like all other _ -as-a-Service packages, AIaaS also makes use of cloud computing – and can add significant strategic flexibility to the operations of organisations, pulling up efficiency and productivity levels. Since AIaaS solutions are typically dynamic and highly adaptable, they also help in optimising the effectiveness of big data analytics. With these ‘readymade’ AI services, it becomes possible for companies to derive all the key advantages of artificial intelligence – without actually having to make huge investments (and bear the associated risks) for building their very own cloud platforms. The onus, however, lies with company CEOs and IT specialists to understand the precise type of AI service they require, and the potential benefits. AIaaS has multifarious benefits – but it should not be adopted without adequate initial research.

Note: While the popularity of AIaaS is a fairly recent trend, the concept of ‘artificial intelligence’ is far from being a new one. At present, we have vendors that offer multifunctional digital platforms powered by machine learning (apart from general cloud AI service providers).

  1. Will AIaaS emerge as a worthy substitute of human intelligence?

    The comparison is an erroneous one to begin with. Contrary to what many think (and indeed, what the concept of AI has meant for years), artificial intelligence is not ONLY about replicating the capabilities and (probably) the cognitive prowess of human beings. Instead, AI should be viewed as an end-to-end technology – which uses various techniques and modules to analyse data better, identify patterns and trends, and calculate the probabilities of different end results (say, for predictive purposes). Broadly speaking, two different types of algorithms – the deep learning (DL) algorithms and the machine learning (ML) algorithms – are used in full-fledged AIaaS services. The prime objective for implementing AI solutions is to enhance the capabilities of existing IT setups, and allow them to ‘learn’ new functionalities (without additional coding having to be done). The entire artificial intelligence vs human intelligence debate is overhyped, and in most instances, misplaced. The two should ideally complement each other.

Note: The need to collect and securely store big data is going up rapidly for companies. AIaaS makes artificial intelligence tools more accessible – and hence, help a lot in data handling/management requirements.

  1. What are the main types of AIaaS?

    For AI to indeed deliver the desired results, enterprises have to select and correctly deploy the ‘right’ type of AIaaS first. Doing so, in turn, requires the IT managers to be aware of the different types of these ‘ready-to-use’ AI services. Broadly, there are 4 different forms of AIaaS: first, there are the customised machine learning (ML) platforms and frameworks, that can create data models and and can ‘read’ patterns from existing data pools. Next up, there are the AI-powered bots – powered by the ever-improving natural language processing, or NLP, capabilities (in fact, chatbots are the most popular use cases of AIaaS). Then, we have the entirely managed ML services – which make use of drag-and-drop tools, cognitive analytics and custom-created data models to generate more values (compared to the general machine learning frameworks). The fourth type of AIaaS includes the third-party APIs (application programming interfaces) – which are built to add extra functionalities to any new/existing application. All that organisations willing to join the digital transformation revolution have to do is identify the type(s) of AIaaS that are likely to boost ROI figures, purchase them from AI vendors, and start implementing them immediately. Small changes, if required, can also be made.

Note: Apart from Microsoft, Amazon and Google, several other companies – like SalesForce and Oracle – are also highly active in the AIaaS space.

  1. How fast is the AIaaS market growing?

    As competition rates are increasing and digital technology is getting more and more refined, the AI-as-a-Service sector is growing rapidly (~$11 billion in 2023). From a $4810 million valuation last year, the global market for artificial intelligence will jump to well over $88500 million by the end of 2025. The growing demand among organisations for using cutting-edge machine learning services on the cloud is also pulling up investment figures. A recent report estimated that overall expenses on AI will show a 4X increase between 2017 and 2021 – as different industries start to adopt AIaaS solutions. The biggest advantage of AIaaS is it allows enterprises and workers to focus on their core capabilities/lines of business – without having to worry about model building or cloud network development. Over the next half a decade or so, the growth of AIaaS will further gather momentum – and developers will be increasingly incorporating AI capabilities in both applications and big data systems.

Note: An enterprise-level study found that 8 out of every 10 companies prefer using multi-cloud models. Among them, specialised hybrid cloud services are the most in demand.

  1. Does the AIaaS market have different segments?

    The scope of artificial intelligence in general, and AIaaS in particular, is huge. As such, trying to understand everything about the service at one go can be complicated, and in fact, an exercise in futility. For purposes of research clarity – the AIaaS domain is divided in different segments, based on different parameters. According to functionality, there are the ‘managed services’ and the ‘professional services’, while from the technology perspective, we have the DL and ML services on one hand, and high-end NLP capabilities on the other. AIaaS can also be segmented in terms of the software tool(s) that lies at the heart of it – web/cloud APIs, processor tools, data archiving and storage, and others. In terms of usability, AIaaS is finding rapid adoption in different industry verticals – right from retail services, transportation, and banking & finance, to healthcare, manufacturing and telecom services (the impact of AI services on the public sector is also going up gradually). A wide range of customisations are also available, enhancing the usability factor of AIaaS.

Note: In the transportation sector, AI-as-a-Service can be used to make tasks like navigation, finding the fastest routes, and parking, simpler than ever before.

  1. What advantages does AIaaS deliver?

    The benefits of deploying AIaaS have a lot in common with the general advantages of any consumption-based (i.e., on-demand) software service. For starters, the seamless scalability is a big factor – since this allows enterprises to start off small, and then increase the scale of AI operations over time (according to project-specific requirements). In a scenario where the need for super-fast graphical user interfaces (GPUs) and parallel machines is going through the roof, AIaaS comes in handy – since it makes it possible for IT managers to implement and use the latest AI-powered infrastructure, without having to be concerned about the lofty expenses. Since AI-as-a-Service is, by definition, ready to use – the challenges posed by the relatively complicated nature of traditional AI solutions are bypassed. Yet another factor in favour of these off-the-shelf AI services is the complete transparency. Users have to pay only to to the extent of their use of the services – instead of arbitrary amounts and high overheads. Smarter AI-powered operations at easily manageable budgets – that’s the key for AIaaS for delivering value to enterprises.

Note: Machine learning plays a mighty important role in facilitating ‘intelligent optimisation’ for different industries.

  1. What factors are driving up the demand for AIaaS?

    Ours is a data-driven environment, and in here, the value of real-time decision-making capabilities can hardly be overemphasised. This, in turn, serves as a key driver of AIaaS solutions. The volume of data obtained from specialised, smart sensors, UAVs and different types of IoT applications is expanding exponentially – and the need of the hour is for improved, intelligent data management, use, accessibility and security. AIaaS is ideal for smarter big data management, as well as for helping computing systems perform specific tasks (with the help of ML modules). Since these services are available as ready-to-use packages from vendors, the development/deployment time is minimised. The fact that AIaaS can be used by practically everyone (thanks to the user-friendly underlying algorithms) also boosts its demand. The growing need for faster GUIs, and customised APIs also acts as an important driver for this market. For cloud providers in particular, and for businesses in general, AIaaS can deliver significant competitive advantages.

Note: The Distributed Machine Learning Toolkit by Microsoft allows users to run multiple ML applications simultaneously. Predictive analytics, speech recognition and translation services are included in the Google Cloud Platform. IBM has its very own Watson Developer Cloud.

  1. Will growth of AIaaS increase the demand for specialist data scientists?

    Yes, and in a big way. What’s more – as AIaaS starts to become mainstream, more time and higher budgets will also need to be allocated. Given the heavy investments (maybe not at the start, but certainly in the long-run) involved and the potential benefits, it is only natural that companies will ramp up their search for IT professionals with high expertise and a lot of relevant experience. These data scientists will be responsible for working with different types of customised AI algorithms. Over the years, AI solutions have mostly been used by the largest players – simply because others did not have qualified, adequately trained manpower (and tech generalists were not enough). However, with the proliferation of AIaaS, a new generation of AI data scientists will appear – and companies of all sizes will be able to hire them and take advantage of artificial intelligence/machine learning. Make no mistake – AI is a complex technology, and proper qualified personnel are required to handle it.

Note: Amazon Web Services is still the market leader in the public cloud domain. However, Microsoft Azure is growing the fastest in this sector. Google Cloud and IBM Cloud occupy the third and fourth spots respectively.

  1. Are there any challenges/barriers for AIaaS?

    For all its advantages and relative ease of use, there are certain points of concern about AIaaS (like any other new tech service!). Since users have to depend on third-party AI services for the data/results/information required, unforeseen delays can crop up. The greater reliance on external service providers can also pose data security challenges – since quite a lot of business-critical data have to be shared with the third-party vendors. The key here is to ensure that the chosen AIaaS has robust security and data governance standards, to rule out unauthorised access. Once we go beyond the initial cost-advantages of AIaaS (over traditional AI), the chances of expenses going up in the long-run – as the technology gets more refined and more complex – also become apparent. Since the vendors provide AIaaS as a package offering, it is impossible to really understand the internal AI mechanisms – although the data inputs and the expected results are known. As a result, the overall transparency of the AI services gets reduced. Over the next few quarters, the technology will get more advanced, and we can reasonably expect that most of these challenges will be satisfactorily resolved.

Note: Serverless technology is leading the way in cloud service adoption. Container-as-a-service (CaaS) is also fairly popular.

     10. How important is it to select the right AIaaS for business?

Let’s just put it this way: if a AI service is implemented without adequate background research, the entire thing can turn counterproductive. At the very outset, a company has to take a stand on whether it at all needs AIaaS solution(s). A thorough comparison between AIaaS platforms and self-coded implementations also needs to be done – to get a fair idea on which option will be more suitable. Users also need to continuously test the AI services, to make sure that they are performing at optimal levels. In any AIaaS, the process of implementing the algorithms is not explained – and that makes thorough AI testing all the more important. In ‘low-level APIs’, there can be glitches in the process pipeline – which need to be identified and removed quickly. As already highlighted above, awareness of the different types of AIaaS, and their respective functions and utilities, is also an absolute must. AIaaS is a vital cog in the digital transformation journey of enterprises – but only if it is chosen and implemented correctly.

Note: According to a research report, nearly 36% of all the expenses on cloud services are wasted. Going forward, the focus has to be on reducing this figure.

      11. How about the importance of AIaaS in the public cloud?

A 2018 RightScale report found that, 67% users are set to increase their spendings on cloud services by at least 20% (18% companies have plans to double their cloud expenses). The adoption of AI-as-a-Service is rising across the board in the public cloud – with both AI data practices as well as AI computing capabilities developing continuously. The recent advancements in neural networks and deep learning mechanisms are also instrumental in pulling up the adoption of AIaaS in the public cloud space. Cloud vendor companies are offering ready-to-use APIs which do not require elaborate machine learning models – enhancing the convenience factor. In the public cloud, AI services can broadly be classified under three heads: cognitive computing, conversational artificial intelligence, and custom cognitive computing. The AI data infrastructure, on the other hand, includes RDBMS, Data Lake and NoSQL.

Note: Cutting down on total expenses is the biggest point of concern for cloud users as present. Generating better financial reports and porting more workloads on cloud are also things that are being focused on.

       12. AIaaS: The future

In terms of adoption and market share, North America (with a 46% share) is the clear leader in the global AIaaS sector. Europe, with ~28% share, occupies the second position, followed by the Asia-Pacific. There is also a definite ‘gap’ in how the services are being used – since only around 33% of the ‘AI companies’ actually leverage artificial intelligence in any meaningful way. In the next couple of years, more users will ‘understand’ the potentials of AIaaS and the far-reaching scopes of the technology – and the deployments will be more effective. The market for web APIs and cloud APIs is set to witness healthy growth, while the NLP market is also on an upward spiral ($21+ billion by 2025). The markets will continue to grow, and as the technology becomes more nuanced – we are sure to see more interesting use cases for specialised AI services.

More than 60% professional marketing experts feel that artificial intelligence is the most important element in their overall digital strategies. AIaaS makes the technology easily accessible – with users being able to enjoy the benefits at a much lower cost. Of course, to truly generate value and improve ROI figures, AIaaS has to be used smartly (with in-depth research). According to reasonable estimates, AI services can push up productivity by up to 40%.

The AIaaS market will continue to grow stronger in the foreseeable future. It remains to be seen how companies manage to use it as a key differentiator, and stay ahead of the competition.

 

Top 12 Trends In Digital Transformation To Watch Out For In 2019

 

Digital transformation trends

 

In the United States, the total revenues from the digital transformation market will go beyond $1.1 trillion by the end of this year. Moving on to the Middle East – experts estimate that digital solutions will augment annual GDP figures by well over $93 billion. The world of technology is evolving constantly – and things that were, even half a decade (or less!) ago possible only in the realms of fantasy, are actually being deployed in the real world (think about roads with ONLY driverless cars, and you will get the picture). The internet of things (IoT) will continue to be the face of this digital revolution, with cloud technologies, artificial intelligence, and AR/VR all becoming smarter, more usable, and more targeted towards addressing real-life problems.

For all the focus and discussion about digital transformation worldwide, there still remains a definite gap between awareness and implementation in this domain. While, on average, 9 out of every 10 entrepreneurs believe that full-blown digital strategies can deliver competitive advantages to their businesses – <20% actually have proper plans and funding schemes in place (less than 10% enterprises are ‘fully digital’). From blockchain and edge computing, to IoT, big data, analytics, AI chatbots and stronger digital integrations – there are lots of avenues for the digital economy to grow further over the next few quarters. In what follows, the most important digital transformation trends for 2019 have been listed:

  1. AR applications to soar

    For all its exciting features and sheer ‘newness’ of virtual reality (VR) – the fact remains that VR has limited usability in the real-world, apart from high-end gaming. In 2019 and beyond, it is going to be augmented reality (AR) that will drive the digital world forward. Already, the demand for specialised enterprise AR applications (say, for training) is on the high – and going forward, this technology will further gather momentum. The key here is that AR has both the innovativeness AND the practical usability (unlike VR, where the usefulness is rather restricted). As the technology gets more and more refined, we are likely to witness a surge in the number of use cases for AR. New augmented reality and mixed reality (MR)-powered products/kits are set to be launched over the next few quarters, and there will be an increased need for experienced AR developers.

Note: Mobile AR is going to lead the way, even as the market for AR headsets also continues to grow steadily. Extended Reality (XR) – a mix of VR, AR and MR – will be the newest tech buzzword.

  1. Focus on delivering improved digital experiences to users

    Digital transformation is, or at least should be, all about providing seamless end-user experience to everyone. That, and that only, can bolster customer satisfaction and customer-retention rates. An improved digital ecosystem also needs to include better workplace experiences for employees, partners, and other stakeholders. In the next few quarters, many organisations will start investing big on new tools, digital methodologies and overall infrastructure – in a bid to make their enterprise IT architecture more robust. There is still a major gap in the scalability of digital experiences delivered by many companies – and as the importance of technology and tech transformation for business acceleration is realised, organisations will look to plug this gap. Investments on digital activities for enterprises will go up fairly rapidly in 2019.

Note: AI-powered ‘intelligent assistants’ and IoT will boost the customer-experience factor (CX) for the new-age, ‘smarter’ buyers.

  1. Digital transformation from the top down, finally

    It is almost impossible to attain digital maturity without expert management. While the different ‘C-suite personnel’ (CIOs and COOs and the like) generally handle the digital ecosystems and IT infrastructures in a company – 2019 will probably be the year when the CEOs start taking greater responsibility for the digital future of their respective organisations. Apart from being more effective, this move will be in line with the preferences of general employees – who typically like the digital directions to come from the top-level. As the CEOs start taking greater control, the ‘C-suite’ officers will gradually move to the background. More importantly, the myth that digital initiatives are something that only the IT or the marketing departments need to be concerned with with will be busted. The onus will be squarely on the entrepreneurs/CEOs to make the right recruitments (for greater business agility, specialisation and digital transformation). The importance of acquiring more reliable data, and upgrading the skillsets of existing employees, also has to be identified.

Note: On a YoY basis, the role of CEOs as the face of digital transformation has jumped from 22% to ~40% in 2018. The importance of CIOs, on the other hand, has gone down to 16% (from 24% last year).

  1. Chatbots to find greater acceptance

    The performance of AI-chatbots for business has come under scrutiny several times over the last few quarters. What’s more, there is also a cloud of uncertainty over how widespread adoption of chatbots will affect employment (i.e., whether there will be major job-displacements). Even so, the growth and improvement of chatbots will continue to be one of the strongest digital transformation trends for 2019 – with 4 out of every 10 big companies adopting chatbots before the end of the year. The ongoing advancements in ‘sentiment analysis’ and ‘natural language processing’ (NLP) are making AI-chatbots smarter and more reliable than ever – ensuring that users can get access to deeper customer insights, and provide customised services accordingly. As far as the effect on human workforce is concerned, companies will realise that chatbots need human touch and guidance for optimal functionality (handing over a buyer query to a human executive, for example). Chatbots are NOT meant to be substitutes of human workers – and provided that the necessary upskilling/training takes place – large-scale job losses should not occur.

Note: By the turn of the decade, 25% of all customer service activities will be handled by AI chatbots (also known as ‘virtual customer assistants’).

  1. Move towards more integrated digital endeavours

    Digital transformation, in the truest sense of the phrase, requires considerable investments and retooling. The fact that more than 70% of all transformation initiatives end up in failure is alarming – and one of the biggest reasons for the common failures is the adoption of a half-hearted, fragmented approach. In the next year and beyond, we will see digital initiatives becoming more integrated – and traditional organisational silos being broken down (the adoption of DevOps culture – bringing together the ‘development’ and ‘operations’ departments – is going to play a vital role in this). The benefits of following an integrated approach for digital transformation are immense – ranging right from better planning and development of powerful data models, to more consistent business growth and greater economies of scale. Top-level digital integrations have emerged as serious business imperatives, and in 2019, many companies will launch their very own digital programs and projects.

Note: Nearly 86% of all enterprise decision-makers feel that digital initiatives have to be integrated properly within the next 20-24 months. Fragmented efforts are almost certain to fail.

  1. The hype is over for blockchain technology

    That’s not to say that blockchain is a flop though. The problems here are cropping up from the lack of a single standard method of blockchain implementation. Since the user-requirements also vary widely (finance to marketing to HR, and more) – modifying the technology becomes an unduly complicated task. However, interest in blockchain is definitely rising – and leading players are examining the usability of blockchain technology for use cases outside of financial services and cryptocurrency (for example, transportation & logistics). Contrary to the hefty growth predictions, developments and experimentations with blockchain will continue right through 2019 – and researches on increasing the mass adoption of the technology (a plug-and-play blockchain model should help) will be conducted. The potential of blockchain is huge – but we will have to wait for a few more years before the technology becomes implementable on a large-scale.

Note: The role of blockchain in the internet of things (IoT) will be interesting. As per IDC reports, blockchain will be enabled in ~20% of all IoT deployments, by the end of 2019.

  1. Greater focus on digital education, training and skill development

    For nearly 42% organisations, lack of adequately trained/qualified personnel is a major problem in the road to digital transformation. More often than not, all the importance and focus is placed on the tech aspects of digital initiatives – relegating the ‘people-factor’ to the background. As a result, major skill gaps – together with business culture roadblocks, underutilisation of talents, and problems related to employee mindsets – become apparent, leading up to sub-par enterprise performance and productivity. Over the next couple of years or so, companies will continue to work towards changing their work environments AND upskilling their workforce (along with new hirings of digital specialists). People have to be made aware of the importance of digital transformation, the day-to-day workflow benefits, the procedure for digital deployments, and the changes in workplace culture involved. Greater commitment for training workers – so that they are actually ready (read: have the skills for) to handle digital transformation – is required. Tech advancements and innovations are all very nice – but it is the human workforce that is the biggest asset of any enterprise. Digital initiatives have to be ‘enabled’ by the workers – for them to deliver the desired results.

Note: On a worldwide scale, the total expenditure on digital transformation will go beyond the $3 trillion mark in 2019.

  1. 5G on mobile to become a real possibility

    Let’s face it, the discussions about the ‘lightning-fast’ 5G technology has been going on for a rather long time. Already, several big players, like Nokia, Samsung and Qualcomm, have initiated fixed 5G deployments - with varying success. However, for the average user, not much has changed – and it is hardly uncommon for mobile handsets to fall back to 3G (maybe even EDGE) speeds from time to time (location plays a big role here). 2019 can finally be the year when 5G mobile becomes mainstream across the board – in both urban and rural localities. Companies like Mimosa Networks are paving the way for fixed 5G wireless access (FWA 5G) – and the next stage is surely the arrival of 5G on smart devices (powered by Verizon, ATT, and other major network service providers). It remains to be seen how big the speed advantages of 5G on mobile actually turn out to be – and what improvements need to be made. For iPhone-users, the wait for 5G is probably going to be a few months longer. This year saw rapid progress in fixed 5G, and the next year will be the one when 5G mobile takes flight.

Note: Early adoption of 5G technology is already lifting the sales of Ericsson’s network equipments. The tussle between Samsung Galaxy X and the Huawei 5G handsets next year will also be fascinating.

  1. The rise and rise of ‘X-as-a-Service’

    Salesforce is leading the way in the ‘CRM-as-a-Service’ domain. There is considerable buzz over the ‘AI-as-a-Service’ sector – in which major advancements are expected in 2019 and 2020. We are steadily moving towards a world of consumption based IT offerings – where everything is going to be available ‘ -as-a-Service’. Apart from delivering more customised solutions, such consumption-based digital services will ensure greater flexibilities, end-to-end scalability, and efficiencies at every stage. Not surprisingly, IT experts and CIOs are on the lookout for ready-to-use ‘X-as-a-Service’ tools – to manage workloads better, and generate competitive advantages for their enterprises. In fact, IT-as-a-Service (ITaaS) has already been accepted as a key pillar of digital transformation – thanks to its manifold advantages, like access to latest tech tools & resources, more agile workflows, and considerably shorter procurement cycles. The growth of ‘X-as-a-Service’ will become even faster in the foreseeable future.

Note: There is also a definite trend of trying to reduce technical debt – in the form of fragmented and inconsistent data collections. The open enterprise microservices can come in handy over here.

       10. More effective utilisation of big data

Be it artificial intelligence or machine learning, or simpler analytics systems – the accuracy (and hence, utility) of everything hinges on the quality and availability of relevant, authentic data. While the fact that close to 89% of all available data at present has been created in the last 12-14 months – organisations, on average, manage to use <1% of the total big data available to them. In the coming year, this percentage will, hopefully, go up to 4-5% – as enterprises adopt better data processing capabilities. That, in turn, will take up the value generated by ML applications by several notches. Data is the single-most important factor for smarter decision-making – and organisations have started making a concerted effort to access and analyse data with greater precision. A lot of work remains to be done though – and we have to wait and see what breakthroughs are brought about by players like Microsoft, SAP and SalesForce. The more quickly we understand the potential of big data and start using cutting-edge digital tools for faster, better data processing tools – the faster will we be able to take AI and ML to the next level.

Note: The value of the global big data and related services market will rise to just a shade under $50 billion in 2019.

     11. More reliance on connected clouds

There is a myriad of needs for superior cloud services – right from faster and more secure networking, to cloud-source storage and seamless app deployments. In many cases, relying on only the private cloud or the public cloud spaces will not be enough – and what’s needed is a combination of public, private and data center resources. Such ‘connected cloud’ networks will continue to grow in 2019 – and this growth will depend on the precise business requirements of users. Over the last couple of years, a series of high-profile acquisitions (CloudHealth by VMware, Cloud Technology Partners by HPE) have clearly indicated the rising interest for highly secure ‘connected clouds’. Companies like Alibaba, Google and Amazon are also active in this domain. In the near future, standalone public or private clouds will gradually give way to ‘multiclouds’ – with the latter offering completely streamlined experiences to users. A mix of cloud-based workloads is what we can look forward to in 2019.

Note: Easier system interoperability, adherence to regulatory frameworks, and seamless data portability are all going to be key characteristics of connected clouds.

    12. Digital Transformation is going to be BIG in 2019

We keep saying this every year – and thanks to the rapid technological evolutions – the coming year is not going to be an exception. Apart from the advancements in machine learning and AI applications, the concept of ‘quantum computing’ is also set to pick up pace (market-leaders like Microsoft, IBM and Google have already started working on this). Unmanned aerial vehicles, or drones, are going to find more use cases, while the field of smart agriculture has many innovation opportunities (how about smart poles for agriculture?). In the corporate space, enterprise mobility management (EMM) and growing adoption of digital workspaces are the trends to look out for. Before 2019 is done and dusted, well over 55% enterprises will have ‘off-premise IT systems’.

Note: Products or services that have been digitally enhanced in some way or the other will be used by 1 out of every 2 Global 2000 companies, in 2020.

An increasing facet of digital transformation in 2019 will be the closer-than-ever inter-relations between AI/ML, edge computing and IoT. In particular, the growth of edge computing has a lot to do with the development of smart city applications (cloud-based data processing cannot be used for that). Edge computing delivers the real-time data processing required – and hence, automatically ensures optimal data utilisation. The number of data interactions between the cloud and the edge (in the so-called ‘Fog’) will go up manifold. One thing is for certain: the demand for newer, more powerful connected devices will continue growing exponentially.

     Major improvements in location services are also expected in the next couple of years or so. Maximum emphasis will be placed on sustainability, security and enhanced operational efficiency of the enterprise ecosystems. While the private sector will continue to be the main beneficiaries of innovative digital initiatives, the impact on the public sector (i.e., smart city applications, smart public utilities) will also increase. In a nutshell, digital transformation is going to disrupt how we work, how we interact, how we spend our leisure…indeed, how we live!

Machine Learning in 2019: Tracing The Artificial Intelligence Growth Path

 

machine learning 2019 trends

 

The age of the ‘intelligent assistants’ is well and truly upon us. Machine learning (ML) has already emerged as one of the key elements of global digital transformation – with cumulative investments (on artificial intelligence and ML) projected to reach $58 billion by the end of 2021. In the US alone, the market for deep learning software will jump from $100 million in 2018 to a whopping $935 million in 2025. The worldwide machine learning industry is growing at a CAGR of ~42% , and will be worth just a shade under $9 billion by the third quarter of 2022.

In the enterprise space too, the growth of machine learning use cases has been remarkable over the past few years. Total enterprise-level adoption of ML tools and solutions is expected to touch 65% before the end of the decade – and spendings will go up to $46 billion (according to a IDC report). On average, 55% corporate CIOs have identified ML as one of the core priorities for business acceleration. Over here, we will highlight how machine learning will continue to evolve in 2019:

  1. Newer use cases of ML are coming up

    Earlier this year, it was announced that the US Army will be using customised machine learning software tools (created by the Chicago-based Uptake Technologies) for predictive maintenance of combat vehicles. In other words, ML would be able to indicate when, and what type of, repair services a vehicle might require at any time. This ‘intelligent’ functionality will be powered by advanced sensors embedded in the vehicle engines. Yet another interesting use case of ML is the prediction of stock market fluctuations – based on the records of previous stock earnings. A recent research showed that such stock market predictions with ML have a 60%+ accuracy meter – which is impressive enough. Moving over to medical science and healthcare, ML models are being used to estimate the probability of death of a person (the accuracy in this case is well over 90%). Progresses are being made to expand the scope of ML further, in retail, marketing & sales, and industrial/manufacturing sectors. ‘Reading’ and ‘interpreting’ past data for forecasting the future – that’s the essence of machine learning – and the technologies are definitely getting more refined.

Note: The concepts of AI applications and ML tools are no longer limited to external robots. Instead, they have become natural extensions of business workflows and everyday applications.

  1. Adoption of ‘hardware optimised for ML’ set to rise

    2019 might very well be the year when specially prepared silicon chips – with custom AI and ML capabilities – become mainstream, at least for enterprises. The market for AI-optimised hardware will continue to grow rapidly in the foreseeable future. A series of new, powerful processing devices will be launched – and we would also get to see high-end CPUs and GPUs being used. Taken together, these tools and platforms will enhance the usability of ML hardware in a big way. In 2018 Q1, SambaNova Systems – an AI chip startup – raised a massive $56 million in a Series A financing round. By the end of 2025, global sales of AI-powered hardware will cross the $120 billion mark. The biggest of players – from Nvidia and Google, to IBM – are already in the game, and the machine learning hardware market will be one to look out for next year and beyond.

  2. Cloud adoption to rise with ML

    A yearly growth rate of ~25% will see the worldwide cloud computing market soar to $410 billion+ by 2020. The growing adoption of ML in enterprises is a key driver behind this surge. For the successful implementation of a ‘machine learning culture’, businesses have to focus on innovation more than ever – with particular emphasis on improved cloud hosting and infrastructure parameters. Over time, more and more ‘AI-specialised tools & systems’ (apart from business critical information and big data) have to be stored on the cloud – and the latter needs to have adequate security and usability standards for the purpose. A robust, scalable cloud support will help enterprises seamlessly move on from machine learning to deep learning, deliver greater value to end-users, and improve their ROI figures.

Note: Starting from 2019, the general user will start to get a clearer idea on how AI and ML processes work – thanks to the detailed ‘AI audit trails’. Given the critical nature of the domains (say: medical science) in which AI is making its presence felt, it is only natural that people would want to know how the technology arrives at its conclusions/predictions.

  1. Moving ahead with capsule networks

    For all the merits of neural networks, they often do not factor in the relative orientation or the position of select objects. As a result, ‘information gaps’ might remain in the machine learning models based on them. To tackle this, capsule networks have already arrived – and they are likely to replace many conventional neural networks in 2019 and beyond. In terms of performance, these capsule networks are a cut above the traditional neural network systems – with more accurate pattern-detection capabilities, and that too, with lesser data and a much-diminished probability of errors. What’s more – capsule networks do not require repeated training iterations either, to ‘understand’ variations. The size of the overall neural networks market will be more than $23 billion in 2024, and capsule networks will be right at the center of this growth.

Note: Advanced healthcare modules based on ML algorithms, for the comparison of medical images of a patient with that of others, are already being used. AstraZeneca, a biopharma company, has plans to use robotics and machine learning extensively – for developing smart diagnostics systems in China.

  1. Rise and rise of AI assistants

    Siri and Google Assistant and Alexa have become pretty much a part of our everyday lives, right? In another five years or so, the value of the worldwide AI assistant market will touch $18 billion. More importantly, each of the top ‘intelligent assistants’ are becoming smarter, on a year-on-year basis (on the basis of 5000 general questions, Siri managed to answer around 31%, among which nearly 80% were correct responses; in the same survey, Google Assistant answered over 67% questions, with an accuracy of a shade under 88%). With the scope of machine learning expanding, AI assistants are ready to move beyond the smart homes and users’ pockets. From the next year, Hyundai and Kia will start to provide built-in, AI-powered virtual assistant systems in their new car models. These assistants will be able to perform a myriad of tasks – ranging right from remote home and car control functions (through voice), to destination suggestions (based on previous preferences) and navigation guides. In all scopes of life, ‘intelligent assistants’ with ML capabilities will be making lives simpler than ever before.

Note: Smart chatbots (with artificial intelligence) are also witnessing rapidly rising adoptions. There is, however, cause to be wary – since biases in training datasets can cause serious damages in user-experiences. The ‘Tay’ chatbot by Microsoft is a classic example of such a failure.

  1. Developers will focus on solving more ‘real problems’ with ML

    When it comes to a fancy technology like artificial intelligence (multipurpose drones and automated surveillance cameras and self-driving cars, and the like), it is very easy to go overboard. However, it is important to realise that – while all of these things CAN become a reality – the steps towards a full-fledged data-driven ecosystem have to be gradual and systematic. In 2019, app developers and AI specialists will be eyeing to use machine learning to successfully address real, important needs (personal and business) – instead of simply churning out new prototypes of deep learning tools. Put in another way, developers have to understand that AI and ML are much more than just a couple of tech buzzwords – and when implemented properly, their potentials can be endless. There are many other technologies that are vying for attention at present (4d printing immediately comes to mind), and unless the developments in AI solve actual problems – investors might start looking elsewhere. It will be crucial to separate the ‘AI overhype’ from the ‘AI facts’, and act on the basis of the latter.

Note: In a recent study, it was found that 89% of all CIOs have plans to implement ML tools and applications in their businesses.

  1. World of the robots?

    Okay, that sounds a bit too dramatic, doesn’t it? In truth though, the roles of intelligent robots in workplaces are gradually increasing – and the improvements in ML are the primary cause for that. In Japan, three-fourths of all elderly care services will be delivered by AI-robots by 2025 – replacing human caregivers. Tianyuan Garments – a China-based t-shirt company – has plans to use ‘sewing robots’ at its Arkansas factory. In general, many labour-intensive tasks (particularly the repetitive activities that do not require much specialised skills) will be performed by ‘intelligent robots’ in the not-too-distant future. Apart from making workflows smarter, improving availability and reliability, and shortening the time-to-market, ML-powered robots would also significantly bring down operating expenses (as well as outsourcing costs, if any). Greater productivity should be a direct result of full-blown AI adoption at workplaces.

Note: Machine learning can also play an important role in precision farming. Smart poles for agriculture, with deep-root sensors and dedicated ML module(s), can help farmers take more ‘informed’ decisions.

  1. Voice technology to the fore

    Whether ComScore’s prediction of 50% of all search activities to be powered by voice by the year 2020 comes true remains to be seen – but there is no getting away from the fact that speech recognition (and interactions based on that) has emerged as an important element of machine learning. Unlike the early days of voice technologies, present-day speech recognition has a sub-5% error rate – which is more than serviceable. Interactive voice response (IVR) systems are becoming smarter than ever – thanks to iterative learning, and voice-based ML systems have the capability to transcribe a wide range of languages/accents. The trend of developers coming up with voice technology-powered mobile applications is also expected to gain further momentum in 2019. Already, assistants like Amazon Alexa and Google Home ‘understand’ our voice commands – and they are paving the way for more such platforms to enter the market.

Note: The traditional, suited customer service executives are also being gradually replaced by virtual characters. The latter offers more prompt responses – and since the conversation is intelligent (virtual agents learn from previous conversations), the personal touch is not lost.

  1. AI markets in USA and China – the big fight?

    North America has traditionally been the frontrunners, as far as artificial intelligence research and adoptions are concerned. This stranglehold, however, is growing weaker and weaker – with the Chinese market emerging as a serious force. In 2017, AI startups in China had a higher equity funding share than their American counterparts (48% vs 38%). The Chinese AI startup scene is holistic (unlike the slight fragmentations in the North American markets) – with the focus being on logistics, smart city projects, retail, healthcare, smart farming, and other domains. When it comes to deep learning too, China is clearly edging it – with 6X more patients issued than in the US. As per reports, China is looking to be at par with the American AI scene by 2020, and emerge as the undisputed leader of ML technologies within a decade of that. It will be fascinating to see how the US vs China race for global AI/ML supremacy pans out over the next couple of years.

Note: Instead of relying on third-party APIs, developers are increasingly turning to making their very own APIs for ML applications. There are plenty of developer-friendly assembly kits and mobile SDKs to provide the necessary help.

    10. More machine learning platforms (and better ones too?)

Platforms like TensorFlow, H2O, ai-one and Torch are already making a difference to how ML functionalities can be deployed in different scenarios. In the year coming up, we can reasonably look forward to more powerful ML platforms – with cutting-edge analytics, classification and predictive capabilities. The capacity of these platforms work with other APIs and big data will also continue to improve. The constant developments in machine learning are opening up opportunities for computers and mobile devices to ‘learn’ faster and ‘interpret/analyse’ data in a better manner. In a February 2018 Gartner report, the total available market (or, TAM) of machine learning at the end of this decade was valued at nearly $26 billion.

Note: AI/ML applications are also facilitating automated decision management practices. Informatica and UiPath serve as great examples of this.

    11. Revolutionising the way humans interact with technology

They might be present only in a handful of locations at present (<10) – but the ‘cashierless Amazon Go’ stores are completely changing the concept of shopping. In fact, by 2021, more than 2000 ‘Amazon Go’ stores might be present in the US alone. The manner in which we deal with, interact with, live with smart things (in particular) and technology (in general) is being shaped by the AI & ML revolution. Be it for a business, or for the society (read: surveillance cameras, smart city applications) or smart homes – deep learning is set to disrupt our lives everywhere, ensuring better performance across the board. Things that only seemed possible in sci-fi movies and our imaginations have been rendered possible with artificial intelligence. The key here has been the adaptability of the technology for different types of use cases. ML is solving problems and delivering value – and that’s precisely why it is growing in popularity.

Note: The development of ‘killer robots’ for warfare can be, potentially, alarming. A recent report predicted that the ever-increasing investments on AI for military applications might very well lead up to a nuclear war between 2040-2050.

     12. NLP to become more nuanced

As a sub-domain of artificial intelligence, the importance of natural language processing (NLP) has gone up significantly over the last few years. By the end of 2020, the global NLP market will be valued at well over $13 billion – with the industry CAGR hovering around the 19% mark. Primarily used for converting data into text, natural language generation is a key feature of many deep learning systems – and for the preparation of detailed market summaries or reports – NLP is extremely handy. The fact that natural language processing has also become highly accurate is also worth noting, and automated systems are being enabled to communicate ideas in a seamless manner. Cambridge Semantics and Attivio are some of the notable companies that provide NLP services.

Note: NLP modules typically need to analyse three things: syntax, semantics and context.

As more progress happens in the world of machine learning and new application areas get unearthed, the demand for AI specialists (rather than tech generalists) will continue to rise. This will, understandably, be accompanied by increases in their average salary figures. There are certain grey areas – like the prospect of mass unemployment and maybe intrusive surveillance – but it is safe to say, 2019 is going to be a big year for machine learning. AI-as-a-Service has arrived!

Sydney vs Singapore – The Race To Become The Next Silicon Valley

Startup scenario - Sydney vs Singapore

 

Silicon Valley and New York might still be the most attractive locations for startups, but the competition coming in from the APAC countries is growing intense. Over the last half a decade or so, total startup fundings in the Asia-Pacific have been on an upward trend, while that in the US have been slightly tapering off (venture capital funding was ~41% for both locations in 2017). China has emerged as a serious ‘startup haven‘ to reckon with – while both Singapore and Sydney (NSW, Australia) have buzzing startup scenes.

In terms of local connectedness opportunities for startup founders, both Sydney and Singapore are located in the top ten list of cities worldwide. While the former accounts for nearly half of all the startups in Australia, Singapore too boasts of well over 2000 startups. In fact, a 2017 Startup Genome report placed Singapore right at the top in terms of startup talent/innovation availability. In what follows, we will do a point-by-point Sydney vs Singapore comparison, and find out which of the two cities offers bigger advantages to startups:

  1. Sydney benefits from natural resources; Singapore focuses on innovation

    Compared to Sydney in particular, and Australia in general, the total volume of natural resources available in Singapore is much lower. The sheer extent of readily available resources give Sydney a headstart – a significant competitive advantage to the startups over here (particularly those in the primary sector). On the other hand, in Singapore – the emphasis is more on making the most from the relatively scarce resources. This is precisely where the importance of innovation – for engineering and biotech and advanced manufacturing – comes into the picture. Given its small size, the growth of Singapore as the most competitive Asian business nation has been nothing short of remarkable.

  2. Which sub-sectors are thriving in Sydney and Singapore?

    The multi-dimensional startup ecosystems of Singapore and Sydney make both of them great places to do business in. Fintech leads the way in the two locations: on average, 6 out of every 10 fintech companies in Australia are Sydney-based, while Singapore is home to nearly 300 fintech startups. The digital media business sector has also taken off in a big way in Sydney and Singapore – with the former serving as the headquarters of multiple leading media companies (the Australian digital media market will be worth >48 billion by the end of this decade). In Singapore, reports show that one-tenth of all VC funding in the last 6-7 years have gone to the digital media sector. Apart from these, adtech is the other dominant startup sector in Sydney (even though the growth rates of the advertising industry at the national level have been flat) – while big data & analytics startups in Singapore have received more than 5% of the total local VC investments. There is room for startups from different sectors to enter the two markets and earn big.

  3. Co-working spaces and the cost factor

    Both Sydney and Singapore have close to 2000 registered startup companies, with the Asian city-country having a slight lead (1800+ vs ~1600 in 2016). However, with close to 50 coworking spaces, Sydney has an edge over Singapore, where around 30 coworking spaces can be found. Australia is the more expensive place to start off a new business too with nearly 3X higher office rent figures ($107000 vs $37000) and considerably more pricey office spaces ($85/square feet in Sydney; $30-31/square feet in Singapore). The average corporate tax rates in Singapore (~17%) is also quite a bit lower than that in Sydney (can go up to 30%). The governments at both places play a proactive role in the growth of startups over there – with a multitude of favourable policies, tax benefits and other initiatives. For example, the ACE Startups Scheme in Singapore offers easy financial help for entrepreneurs, while the Entrepreneurs Infrastructure Programme of NSW tackles a lot of the networking & finance requirements of Sydney-based startups. The R&D tax incentives implemented in Sydney are also worth a special mention.

  4. Singapore marginally ahead of Sydney for fintech startups

    In 2014, Australia had less than 90 fintech companies. Cut to 2017, and that figure has surged to 590 – underlining the remarkable growth of this sector in the last half a decade. Nearly 60% of these companies are based in Sydney – making the ‘Harbour City’ the ‘fintech hub’ of the country. The fact that fintech investments Down Under are rising at a time of globally declining trends is all the more remarkable. Singapore has an even stronger fintech ecosystem – with close to $990 million being invested on this sector in 2017 alone (in 2016, Australian fintech sector received $670+ in the way of investments). Wealthtech, payments and lending are the three fintech startup categories that are growing the fastest in Sydney. Silot and InstaReM are two of the leading fintech players in Singapore.

  5. Business environment

    There is a lot in common, when it comes to the basic business legalities for startups in Sydney and Singapore (both taking features from the UK system). The two locations offer uniformly conducive environment for business – facilitating new entreprepreneurs to kickstart their businesses here. However, Singapore once again has slight advantages in this regard. While there is little to separate the countries in terms of ease of starting a business (in a World Bank report, Singapore and Australia occupy the 6th and 7th slots respectively) – Singapore offers more protection to minority investors, and has easier procedures for business contract enforcements as well. It’s not for nothing that Singapore has remained the ‘easiest place to do business’ globally right through this decade. Sydney, with all its startup-friendly policies and venture capital availability, comes in at the 15th spot in the World Bank study.

Note: The border clearance processes of Singapore have also been recognised as the most transparent and efficient in the world.

  1. Singapore has the ideal infrastructure; Sydney has some catching up to do

    From space allocation and mentorship, to incubation and business acceleration, the government of Singapore offers specialised assistance to startups at various stages of growth. The Australian government (the NSW authorities in particular) have a similarly supportive attitude – but according to many entrepreneurs, there are still gaps in the day-to-day interactions between the government and the Sydney startups. What’s more, life is just that bit easier for venture capitalists in Singapore – since funds can be obtained from the government, with an expected return as low as 5-6% (in other wards, Singapore has ‘more VC funds’ than Sydney). The Australian startup hub definitely has the more naturally innovative minds – but the inherently risk-averse nature of many Aussie investors are somewhat holding things back. Political stability, peace and timely assistance are bolstering the startup scenes in both Singapore and Sydney – and at present, these helps are making a more telling effect in the Asian island nation.

Note: A couple of months back, AirTrunk – a fast-developing Singapore startup – raised $850 billion as funding, for a business expansion in the APAC region. Incidentally, the company also has centers in Sydney and Melbourne – and has plans to pump in funds in these centers too.

  1. What are the entrepreneurs thinking?

    Understanding the mindset and the thought processes of the business entrepreneurs/founders at any place is a great way to predict how the startup scenario will pan out over the long-term. According to the 2018 Startup Genome report, more founders in Singapore has the typical ‘entrepreneur mindset’ (32% vs 24%) – while those in Sydney have a slightly greater inclination to emerge as ‘business builders’. In terms of ambition, drive and hunger for success though, Australian business owners are a step ahead of their counterparts in Singapore (31% of Aussie founders have high ambition levels, while 56% of them wish to make a difference to the world; the corresponding figures for Singapore founders are 18% and 49% respectively). The naturally innovative nature of Sydney-based startup owners becomes apparent by the fact that only 30% of them have ‘relevant experience’ in their respective sub-sectors. In Singapore, this figure is as high as 44%. One thing is pretty much clear – neither at Sydney nor at Singapore is money-making the sole prerogative of the startup-owners. Many of them actually want to ‘change the world’ with their business.

  2. Tax rates and incentives in Sydney are great; but Singapore is even better

    Apart from the much-lower average corporate tax rates in Singapore, the Asian location also has the more favourable income-tax (IT) structure. The cap on the progressive personal income taxation in Singapore is at 22%, while in Australia – the IT rates can go up to 45%. The single-tier corporate tax system in Singapore is also simpler (and rules out chances of double taxation) – while in Australia, dividends are also taxable, according to the ‘franking credit’ (tax amount paid by company) mentioned in the statements. It also has to be kept in find that the 43.5% refundable tax for Aussie startups with turnover <AUD 20 million (under the R&D tax incentive programme) is a major incentive for people looking to start businesses in Sydney. There is, however, a difference in which foreign-sourced funds are managed by the respective governments. While resident Aussie companies have to pay taxes on profits earned anywhere in the globe – the profits earned outside of the country are not taxable in Singapore.

Note: In terms of enabling trade (openness to trade), Singapore emerges as the clear winner, While it has the top spot in a 2016 report, Australia is listed at the 26th spot.

  1. Where are the more knowledgeable startup founders located?

    Once again, the numbers are close – but it seems that Australian entrepreneurs, on average, have greater business knowledge than those in Singapore. A recent report pegged the ‘theoretical know-how index’ of Aussie founders at 5.8 – significantly higher than the 4.9 index for Singapore-based founders. In terms of practical know-how too, Sydney edges it – albeit the fight is closer (5.7 vs 5.3). The metropolitan GDP of Sydney (~$335 billion) is much higher than that of Singapore (~$270 billion). This automatically means that the size of the local market is greater in the Australian city. In Sydney, founders also have a greater sense of being part of a community (‘sense of community index → 7.5’). In both the places, founders regularly interact with each other, and strike up mutually beneficial strategic partnerships.

Note: The average salary of a corporate professional in Singapore is around the $3100 figure, slightly lower than the average salaries of $3500-$3600 in Sydney.

     10. Availability of qualified workforce

Human capital is the biggest asset of any startup – and there is no shortage of highly-qualified human resources in either Sydney or Singapore. Nearly half of the total employable population in Singapore hold advanced degree certificates (or diplomas) in their respective fields – while 4 out of every 10 members of the Australian workforce can boast of having tertiary qualifications in their CVs. Finding and recruiting suitable, qualified workers is fairly easy at both places. However, the differences in the work hours and the minimum wage (nothing specified in Singapore; AUD $17.70/hr in Australia) have to be taken under consideration. While Singapore does not allow people to work for more than 12 hours in a day, the maximum work-hours in a week for Australian workers is 38 hours.

Note: The procedures for registering and protecting Intellectual Property Rights (IPR) are more or less similar in Sydney and Singapore.

       11. The flow of startups from Sydney to Singapore

The recent trend of Australian startup companies to expand in Singapore – with a view to nurture and grow their businesses – is interesting. While there is no doubting the merits of the startup ecosystem in Sydney (and, of course, the government initiatives), experts feel that the tax incentives and other assistances are targeted more towards companies in their absolute nascent stages. For startups that are a bit more established, Singapore is probably the easier market to tap into, for funds and collaborative networking, and even customers. There is just a bit of additional bureaucracy in the research support incentives in Sydney, which is not present in Singapore. However, as multiple entrepreneurs have confirmed, startups are NOT LEAVING Sydney in favour of Singapore. Instead, the Aussie companies are looking to streamline and speed up their growth by strengthening their presence in the Asian market.

Note: The Dream Collective, Shootsta and HashChing are some of the major Australian companies that have initiated plans to expand into Singapore.

Sydney is a relatively peaceful city with a charming lifestyle – which adds to its attractions as a startup haven. While Singapore’s lifestyle is probably not as alluring, the stability and peace in the country offers encouragement to entrepreneurs. The inflow of foreign direct investment (FDI) is, understandably, much higher in Sydney, unemployment rates are lower, and the cost of a single-bedroom house is roughly the same at the two places.

Sydney, as has been pretty much well-documented, is a terrific place for launching a startup – particularly tech startups. However, from our discussion above – it is pretty clear that Singapore has certain extra advantages for new businesses. Both the places are certainly in the race to become the ‘next Silicon Valley’, and it seems that Singapore has taken a slender lead in this race.

Top 15 App Ideas For 2019

new app ideas 2019

Are you one of those who feel that the mobile app market is already mature, and is slowing down? If yes, well…there’s news for you! On a YoY basis, the total number of app downloads is set to go up by >15% (205 billion in 2018 vs 178 billion in 2017) this year. Fast forward to 2022, and we will be looking at annual app store revenues in excess of $68 billion – with cumulative downloads going past the 255 billion mark. In terms of app availability, Google leads the way – with ~3.8 million applications available for download by the end of 2018 Q1 (Apple App Store, with 2 million apps, comes in at a distant second – with the Windows Store and the Amazon Appstore further behind). On average, 6100 Android apps and ~1450 iOS apps are launched every day – and there is no dearth of applications showcasing innovative ideas, and using the latest technologies. In today’s discussion, we will highlight some new app ideas for 2019:

  • App for smarter cooking ideas

    Online recipe portals and cookbooks are all very nice – but don’t we often come across otherwise interesting recipes, which include ingredients that are not available at the time? This new mobile application will take away that bit of inconvenience – by suggesting recipes on the basis of the stuff already available in the kitchen. All that the users will have to do is provide a full list of the cooking ingredients ready at hand – and the app will display multiple nice and tasty recipes using ONLY those ingredients. People will be able to vote recipes up and down, and there will also be a special ‘Recipe of the Day’ section (guess what…that will also be according to the ingredients you have!).

  • App for staying safe

    This one will be more in the form of a personal bodyguard app. There will be two options to register – either as a ‘general user’, or as a ‘security provider’. The latter would comprise of ex-policemen or military officers or retired army stuff, set to ensure that the civilians in their locality do not face any hooliganism or crime. Instead of pressing an SOS tab and waiting for the authorities to arrive, a general user – as and when confronted by a problem (thieves, eve-teasers, goons, etc.) – will only have to tap a button, to send emergency notifications to all the ‘security providers’ in the locality (say, within a 20 km radius). One of the ‘security providers’ will take up the job and arrive at the spot to deal with the problem. For women in particular, and anyone in an unknown, lonely neighbourhood in general, this app will offer just that extra level of safety assurance. The app should be made for both iOS and Android platforms.

  • App for finding quality home service supplies

    From pest control services and home heating & cooling equipments (HVAC) to gardening, home cleaning and furnishing services – there are a lot of things that homeowners need to keep an eye out for constantly. What’s more, these services are often not particularly inexpensive either. This new mobile application will look to build a community of local homeowners – who will be able to search and look through discounted home service offerings (posted by local, verified sellers). An individual homeowner will also be able to put up something (or some services, for that matter) for sale. There will be a real-time chat option as well, for users to participate in home decoration and maintenance-related discussions. Think of it this way – you need some plumbing done urgently, and you do not have to tag along to the plumbing store. A few taps on the app will bring you in contact with plumbing service providers, and that too at heavily discounted rates!

  • App for managing money (lent and borrowed)

    Personal finance management is tricky business. Different bills have different due dates, at times we have to borrow money from others (banks & individuals) – while keeping track of the money we lend is also important. Wouldn’t it be just great if there is a digital platform where all these details could be neatly organised and kept updated? That’s precisely what this mobile app (a web version would also be handy) will serve as. Users will have to enter the names of the borrowers and lenders, the respective amounts of money they owe or are supposed to get from them, the installment options, and the due dates. Changes, as and when they occur, have to be updated in the app. This innovative money-management application, on its part, will generate alarms as payment due date(s) approach (both for repayments as well as money receiving) – and will constantly give you an integrated picture of your finances. One glance at the app will tell you how much in the red, or green, you are at any point.

  • App for measuring crowd density

    Going to the coolest pub in town on a Friday night, only to find it overcrowded, can be a huge bummer. However, with the help of artificial intelligence capabilities and smart IoT sensors, we can easily have an app that would do away with such uncertainties. Before visiting any restaurant or pub, or any particular public place, users will be able to check out both the seating arrangements at the place, as well as the live crowd density over there at that point in time. For security purposes though, the faces of the people at that place will not be shown. Armed with the knowledge of how crowded (or deserted!) a place is at any time, the user can now take a call on whether (s)he would like to go over there.

  • App for prioritising tasks

    At home and at work, being able to prioritise tasks efficiently is a must-have quality for anyone. While this comes easily to some, there are many people who need a bit of help for this purpose. There are a few ‘task prioritisation apps’ on the Android platform – but since none of them are quite up to the mark yet – there is an opportunity to come up with an entirely new app (on both iOS and Android). On this app, prioritisation will be done on the basis of pairwise comparison. In other words, a user will have to list his pending tasks in pairs – compare them – and then decide which one is to be given higher priority. Once this is done for one pair of tasks, the next pair will be up for comparison. If a new task comes in, it will be compared pairwise with all the other existing tasks. The priority ordering can also be changed if the opinions of the user change. Once a full priority list is ready, an individual will be able to go about completing tasks systematically.

  • App for dressing up correctly

    All guys would love to dress up like Leonardo diCaprio, and every lady would die to get that Emma Watson look – but that does not always work out (or is even feasible!), right? What we CAN do is doing the best with the clothes and accessories that we already have in our wardrobes. This iPhone application with built-in AI capabilities (can also be made for Android) will serve as a helpful dressing guide. There will be a provision to store pictures of all the dresses a user has in the app (i.e., picture of clothes have to be imported in the app) – and on the basis of the occasion chosen (a business meeting, a cocktail party, a birthday celebration, and the like) – the perfect dress suggestions will be displayed. A user will also have the option to check out a virtual version of him/herself in the suggested dress combination. Instead of having to fumble through clothes and being uncertain about what would go with what – people will be able to rely on this app as his/her new fashion advisor!

  • App for thought reading

    This will be an attempt to take social networking to the next level. Once a user puts in whatever he is thinking of at any moment in the app – (s)he will be instantaneously be able to see whether there are others (fellow app-users, obviously) who are thinking along the same lines in the locality (say, within a 15-25 meter boundary). After finding like-minded people with the same thoughts, the user can send along a friend request to him/her, chat with him/her anonymously, or even schedule an actual face-to-face meeting. Of course, the other person will have the option of rejecting any incoming friend request. Security might emerge as an issue – and app developers have to make sure that users have to complete their profile information – in order to be able to register on the app.

  • App for keeping pets healthy

    There are pet care apps by the dozen in the stores, and we are not proposing to build just another clone of those. This one will be different – since it will only focus on the health parameters and activities of your beloved canine or feline buddy. The quantity, type and intervals of food intake will be tracked, along with heart rates and the amount of time walked or spent in other activities (via GPS). Pet-owners can also get in touch with professional vets instantly through the app, and seek help in case of emergencies. There will also be an option to upload HQ images of dogs and cats on the app, and sharing them with pet-doctors, to get a quick health feedback. Apart from these, there can be a dedicated section for curated, highly informative pet care articles from leading journals. Keeping our pets happy is our responsibility – and this all-new application would help us in fulfilling that better.

  • App for getting the lyrics of a song

    Yes, there are hundreds of sites where you can look up for the lyrics of songs. However, it is pretty common for a tune to just sit in our head – and we can’t help but hum it along. In such cases, not knowing the lyrics – and not being able to search for it (for example, if the tune just comes while driving or while traveling in the subway) – can be distinctly irritating. This iPhone music app will offer a quicker, better solution. The user will have to launch it, move to the ‘Hear Tune’ screen’, and hum the piece of music. The app will identify the tune (by matching it with the huge collection in its database) – and instantly display the lyrics. There can also be a daily challenge section – where the lyrics of a song will be displayed, and users have to sing it in the correct tune.

  • App to plan weekend with buddies

    Let’s take a pause and think – how many of our ‘besties’ and ‘BFFs’ do we actually manage to keep regularly in touch with, once college is over (‘Hi’-s over Facebook do not count)? Not many – and that can’t be helped – given the busy lifestyles of each one of us. The only time to meet up is during the weekends, and an app can be made to sync the fun weekend plans of close, long-term friends. To start off with, a user has to invite friends and create a list of buddies (a community of old friends, so to speak). Once that is done, people can start sharing their weekend moods and plans. Friends who are looking to do something on similar lines can fix up meetings and plan outings, or meals, or games, together. In life, we keep losing friends – and this app will look to ensure that will no longer be the case.

  • App to become an expert in dating

    There is no dearth of mobile dating apps out there. But what if a user looks for a date, finds a very nice person of the opposite gender, fixes a romantic dinner – but then feels stage fright, simply because (s)he is not a good conversationalist? These are the situations that cry out for ‘wingmen’ (as Barney Stinson of HIMYM would refer to them!) – people who can advise on what to say and what to avoid during a date. Simulated conversations on a variety of topics during a date can be viewed (these will be like case study videos!). An individual will also be able to ask specific questions to the experts, and be guided accordingly. Records of a date can be uploaded for feedback. This won’t be just another dating app where singles look for partners – it will be a digital assistant to help users put their best foot forward during those long-anticipated dates.

  • App to make the best use of time

    This will be an iPhone self-help app with a twist. For all the good points about social media and video-streaming applications – the fact of the matter is, many people tend to spend way too much time on them. The new app will serve as a tool…a constant reminder…to get rid of such addictions. It will be able to record the number of minutes a person spends on Netflix or Facebook or Snapchat or Instagram – and then list out a series of alternative things (more productive activities) that could have been done in that time. In terms of economics, the app will help users realise the ‘opportunity cost of time’ that they often fritter away. In the 120 minutes of sitting through an unremarkable movie – a person could have done some yoga, done a bit of cooking, read a book, or even caught up on some sleep. That’s precisely the sort of information this app will deliver.

  • App to keep track of expiry dates

    People buy more stuff than they need to at any time – there’s no two ways about this. Now, these things have certain expiry dates – and if they are not fully used up by that time (so often, they aren’t) – these go to waste. Here is an idea to minimise such wastages, and keep track of all the things that a particular user buys. (S)he has to scan every item with an expiry date (medicines, sauces & ketchups, creams, and others) – for storing the information within the app. As the expiry dates come close (say, from 20 days before the expiry date), the app will generate alarms – indicating the date AND the item under question. Two potential problems will be handled by this app – neither would too many things be wasted, nor will people face the dangers of using any product after its expiry date.

  • App with AR capabilities to scan people

    How much do you know about the person sitting across the table from you? Only the bits (s)he decides to tell you – and maybe the information you manage to gather by ‘Googling’ that person’s name. It would be decidedly more convenient if there is an augmented reality-powered application – that can scan people’s faces, and aggregate all the information available on them on a single screen. Once again, security can be a potential pain point – and only authenticated users will be allowed to use the app. The process is simple – launch the app, point your device at the other person’s face, and get all the information about him/her at your fingertips…in a matter of seconds!

There can be a cross-platform social app for all the grandparents out there, eager to stay in touch with their grandsons/granddaughters (with real-time chat and file sharing options). A dedicated communication app for researchers would allow professionals from across the world – with differing climatic, geographical and economic/political conditions – compare and exchange notes. For tourists, there can be an iOS/Android app for connecting them with verified tour guides – saving them from falling in the clutches of fraudsters.

We are continually moving towards a ‘XXX-as-a-Service’ world – with the benefits of on-demand service apps more evident than ever before. As such, we can reasonably expect more such apps – following applications like Uber and Swiggy and Grofers – to be launched in 2019. New app ideas – with interesting uses of cutting-edge technologies – are being floated, and we can look forward to many innovative mobile applications hitting the stores next year.

Apps slowing down? Not a chance!

Top 12 Mobile App Development Trends To Watch Out For In 2019

 

app development trends 2019

 

The popularity of mobile applications is soaring higher than ever, putting to rest speculations of whether this market has entered a mature stage. While the average per-session app activity duration (i.e., the time spent on apps) grew only by 6% on a YoY basis last year – users are increasingly turning their attention to newer applications, incorporating more innovative technologies that can disrupt day-to-day lives and make things just that bit easier. The old adage – ‘there is an app for that‘ – has never been truer.

This ever-growing interest in new mobile apps has, in turn, resulted in a surge of consumer spendings at the app stores over the last few quarters. By the end of this year, this figure will stand at ~$115 billion, nearly 28% more than the total spendings in 2017. The robust demand figures are also causing professional mobile app developers to come up with newer and better software products in general, and smartphone applications in particular. The app industry is constantly evolving, and we will here look at some interesting mobile app development trends that are likely to dominate in 2019:

  1. M-commerce apps are set to surge

    At the end of 2015, the global mobile payments market was worth $450 billion. Cut to 2019, and that figure will jump to $1086 billion (well over double) – underlining the exponential rate at this sector is growing. In a recent survey in North America, it was found that 2 out of every 3 advertisers/sellers with dedicated shopping applications generate more than 60% of their business leads over mobile. In these markets, 44% of all sales take place via mobile apps – well over the 33% share of desktop (website) and 23% of mobile web. Across the world, more and more customers are completing purchases on their phones – thanks to the ready availability, and robust security, of shopping applications. The growth of m-commerce transactions is also being driven by the high adoption rates of mobile wallets (projected to touch $6.1 billion in value by 2022). In the next year and beyond, expect more m-commerce/shopping apps to be launched in the stores, along with other new mobile wallet applications.

Note: The number of apps with Apple Pay integrations or Google Pay integrations is also set to rise.

  1. Further growth in cloud applications

    The overall Software-as-a-Service (SaaS) market is growing at a mighty impressive CAGR of ~18.2% (2017-2021). The market for cloud applications alone is expected to grow to $68 billion by the final quarter of 2019 – a 123% increase over the corresponding figure in 2014. With memory/storage space and other device-specific limitations becoming increasingly prominent – users are, not surprisingly, showing their preference to store critical, confidential big data on the cloud (once again, security is a key factor over here). Within the next couple of years or so, cloud-based apps are expected to contribute a whopping 90%+ of the total volume of mobile traffic worldwide. Compared to this year, mobile cloud traffic will spike by around 10% in 2019. New software from mobile app companies are almost certain to have seamless cloud storage and support features – with strong authentication/safety assurances and easy accessibility options. The future of mobile apps is in the cloud!

Note: On average, more than 1400 cloud services are used by an enterprise. Clearly, the scope for business cloud applications to grow is huge.

  1. Rise & rise of artificial intelligence and machine learning

    Mobile apps with built-in AI support will become even more mainstream in 2019 and beyond. ‘Intelligent’ digital assistants like Google Assistant, Siri and Amazon Alexa are showing the way – and the impact of ‘robots’ in day-to-day activities will increase considerably in the foreseeable future. Already, 4 out of every 10 business houses make use artificial intelligence, and the more refined machine learning techniques, to deliver optimized customer service (think of the shopping apps with AI-based chat support, to guide buyers along, and even help them complete transactions). A big factor in the rising influence of AI and ML in mobile app development has been the growing popularity of chatbots. At a conservative estimate, chatbot applications can generate yearly savings of up to $7.5 billion for businesses. The value of the worldwide AI industry will go past $1.2 trillion in 2019 – and we will be looking at a bigger-than-ever pool of ‘intelligent applications’. Right from voice search, predictive text for easier typing and GPS route suggestions, to email classifications, quick & correct translations, and email/photo classifications – AI can increase the usability of mobile apps in a myriad of ways.

Note: The demand for personalized app experiences is higher than ever among end-users, and AI can play a big role in delivering that.

  1. On-demand apps will continue to rule

    Apps like Uber and Lyft have completely revolutionized the concept of ‘hailing a taxi’. Food delivery, laundry services, product delivery, cleaning & pest control are some other fields where on-demand mobile applications are making their presence felt. Expect this trend to gather further momentum over the next half a decade or so – with on-demand services becoming available for many other use cases. Scalability, customizability and, of course, convenience are the three pillars on the basis of which the popularity of these applications are growing. Before 2018 rolls to an end, the on-demand mobile app economy will become a $59 billion sector. With constantly increasing user-bases and surging revenues, this sector will go up further in future.

Note: In 2018 Q1, Uber’s revenues jumped by 70% (amidst speculations over the company’s profits). Mobile on-demand apps are already strong…and growing stronger.

  1. Greater focus on ‘smarter’ apps

    The number of total app downloads has undergone a ~5X increase from 2012 to 2017 (57.2 billion vs 255 billion). Keeping pace with that has been the growth of the global market for internet of things (IoT) – from less than $3 trillion in 2014 to almost $8.99 trillion by the turn of the decade. Worldwide investments and spending on ‘connected gadgets’ is set to breach the $1 trillion mark by 2021 (the 2017-2021 CAGR will be more than 14%). From healthcare, energy and retail services, to education, smart agriculture and smart cities – IoT applications are being put to use in many new and innovative scenarios. LoRa technology and blockchain technology are also growing at a rapid clip – and combined with IoT, they can lead to the creation of truly powerful and useful new applications. Lack of complete awareness and specialized skills remain a challenge though – and going forward, the onus will be on professional mobile app developers to be familiar with the latest developments in IoT and smart things. The need to ‘stay connected’ is greater than ever for the average user, and IoT apps can be extremely useful.

Note: There will be >20400 million installed IoT units in 2020. The current figure is around 11000 million units. Consumer apps are the biggest users of the technology, although IoT-powered business applications are also on the rise.

  1. More apps for wearables

    In 2019, the total sales of wearable devices is expected to be well over 250 million units (in 2014, a year before Apple Watch burst onto the scene, the total shipment figure was less than 30 million). On a YoY basis, there will be a 36% growth in the value of the market for wearables across the globe. The remarkable growth in wearable technology is, in turn, revving up the demand for custom apps for wearables. A recent report pegged the 2016-2020 CAGR for the global wearable apps market at 57% – a far cry from the scenario even a couple of years back, when there was a serious dearth of good-quality apps for smartwatches. The launch of free and multi-featured fitness bands/sports bands is a key factor fueling this growth. Apart from smartwatches, the market for more innovative wearables – on-body sensors, smart jewelry, mobile communication tools, etc – is also growing fast. Leading app development agencies have already turned their attentions on making apps for wearable tech – and this trend will continue in 2019 and beyond.

Note: The wearable tech market is projected to breach the $100 billion mark in 2023, and the $150 billion mark in 2026.

  1. Advantages of Accelerated Mobile Pages (AMP) will become more apparent

    Ever since its arrival in 2015, accelerated mobile pages (AMP) has continued to grow. Thanks to the considerably faster loading of mobile pages, problems like ‘lazy loading’ – and related customer negative impressions – have become a thing of the past. In fact, a study found that AMP pages are ~84% faster than regular mobile web pages. The enhanced clickability, improved UX, and strong reliability and availability assurances of AMPs also push up the overall visitor/traffic figures – while minimising the average bounce rates. The fact that AMPs can be displayed in a customised manner on the different browsers – delivering a seamless end-user experience – is yet another big factor. Over the next few years, the popularity of accelerated mobile pages will continue to soar – and for businesses, managing/updating web pages on the go will become easier than ever before.

Note: By 2017, nearly 4.5 billion AMPs had been published. Nearly 30 million domains were in active usage, for creating AMPs.

  1. App security to remain under focus

    Last year, the total volume of mobile malware increased by more than 20%. There has been a series of high-profile software/cloud security breaches – leading to the theft/misuse of private and personal data. The number of malicious applications is constantly rising – and according to a report, by 2019, the frequency of ‘smartphone infections’ will nudge the 1% mark (i.e., 1 out of every 100 smartphones will be affected in some way or the other by buggy/malicious software). In such a situation, it is only natural that concerns over the security and data-safety features of mobile applications are increasing. App-makers and software testers have to realize that, if a user has any doubts over the security standards of an app, (s)he will not download it (and there are hordes of alternatives available). All types of potential risks that a new application can face – right from insecure data storage, absence of state-of-the-art binary protections, and authentication/authorization problems, to injections from the client-side, unforeseen data leakages, DDoS attacks and problematic server-side controls – have to be identified and thoroughly checked. Smartphone-owners, on their part, should know better than to download every new app that hits the store(s).

Note: Increased mobility is directly proportional to chances of security breaches, according to nearly 63% app-users.

  1. Role of AR/VR in mobile app development

    Gone are the days when virtual reality (VR) and augmented reality (AR) technologies were deemed to be for high-end gaming applications only. While apps like Real Strike and Pokemon Go are definitely showing the potential of AR-based gaming, use of applications powered by augmented reality is expanding in both the enterprise space and the consumer space. Asia-Pacific has emerged as a fastest growing geographical area of the global mobile AR market – with the latter slated to reach $80 billion by the end of 2022. Dedicated AR applications will go up by almost three times in the 2018-2022 time span (4680 million in 2022; 1570 million in 2018). By the next year itself, the total count of AR/VR based apps will go beyond 5 billion. Developers have understood the need to deliver more immersive, innovative, 360° experiences to final users – and as such, they are trying to incorporate AR modules in their apps, to drive up engagement levels.

Note: The key here lies in using AR/VR in a way that actually enhances the functionality and value of mobile applications. Using the technology just for the heck of it will not be advisable.

     10. Android Instant Apps are growing rapidly

The launch of Android Instant Apps in 2016 changed a lot of things. For starters, it started giving customers the opportunity to check out the flagship content of any app, without having to download and install the full application. In addition, Instant Apps have also been statistically proven to have reduced frictions in app-usage and app-dropoffs after single use. By the first half of this year, the user-base of Instant Apps had expanded beyond 500 million devices. A common pain point of many Android-users across the world is the lack of storage space on their devices – and Instant Apps solve this problem nicely, since no full installations are required. In March 2018, Google unveiled Play Instant for third-party Android game developers. There are question marks over whether the growing popularity of Instant Apps might have a negative impact on app download figures – but for now, it can be said with confidence that Android Instant Apps are here to stay.

Note: With the help of Instant Apps, Dotloop managed to bring about a 62% increase in user-engagement levels. Jet has also managed to boost conversion figures by nearly 28%.

      11. Beacon technology to play a bigger role

With a projected CAGR of 130%+ for the next half a decade, beacons are probably the sub-sector of mobile technology to really look out for in 2019. The face-off between Apple iBeacon (the leader, with more than 50% market share) and the Google Eddystone platform will be fascinating – with both having multiple innovative connectivity features and high-end capabilities. Within the next couple of years, the world will have over 500 million bluetooth low-energy (BLE) beacon units – and the overall beacons market will race past the $25 billion mark in 2024. Mobile apps powered by beacon technology and strong geolocation support find acceptance in a number of sectors, with the retail industry being right at the forefront (serving as coupon aggregators). By 2020, beacon technology will start to create 1.6 billion retail coupons on a yearly basis. Once again, specialized knowledge and skills will be required to implement beacon tech in mobile applications.

Note: Progressive web apps (PWAs) will also continue to grow in 2019 and beyond, albeit at lower rates. PWAs are relatively less complex, and hence, are easier to develop.

       12. Growing importance of low-code development

Platforms like Zoho Creator, Appian, Outsystems and Microsoft PowerApps are changing the process of mobile app development for a vast cross-section of developers. These are the low-code app development platforms (LCDPs) - and their adoption is already high, and set to grow further over the coming years. This June, Mendix Assist became the world’s very first LCDP powered by artificial intelligence (AI). There are, however, two points of concerns over here: firstly, many of these platforms are not necessarily ‘low code’ per se, but have quite a lot of ‘hidden codes’, which clients cannot see. Secondly, there are speculations over whether LCDPs can ‘replace’ human developers in the long-run (not likely, since skilled coders will always be required to monitor and manage these platforms). The global LCDP market has already moved past $15 million – and by the end of 2022, the value of this sector will be just a shade under $27.5 million.

Note: Nearly 1 out of every 4 LCDP-user starts out with negligible programming knowledge. 71% users, on average, can start making apps with these platforms within a time-frame of 3 months (or less).

Cross-platform app development is yet another thing that will continue to grow bigger in 2019, The market for specialized cross-platform tools is growing at a CAGR of 37% – and platforms like React Native are being increasingly used (iOS and Android). The focus of mobile app developers will squarely be on coming up with top-class UX solutions. Applications that deliver true value AND are easy to use are the ones that will succeed.

These are exciting times in the mobile app market, with the latest technologies (like AI, AR, Blockchain and IoT) ushering in a stage of transition. One thing is for certain though: this market is not going to slow down anytime in the foreseeable future!

 

Publishing Android Application on Google Play

(In this post, a senior Android app developers outlines the process of publishing a brand new application in Google Play Store)

 

Android app development

 

I was wondering how small to medium enterprises are making lots of money with a single app. Yes, it is 100% true. These days, people spend almost 2-3 hours in a day on mobile applications rather than websites. The reason is straight and simple: apps are fast processing, user-friendly in nature, offer enhanced visibility and customer experience etc. Believe me, even I started my app journey a few years ago and till now I’ve collected a great (and varied!) deal of experience. So what are you waiting for? Take a step forward towards your dream and mark your valuable presence in digital world by building your app.

If you are planning to learn the basic to advanced phases of application development journey, then you can participate in the Android Development Course accessible over the web from anywhere anytime.

Publishing an Android application is a method for making your products visible to users so that they can use, download or suggest improvement and submit feedback without any interruption. Publishing is the last step involved in the Android development process.

Once you have finished and done with final testing of your Android app, you can sell or distribute it freely to the users with Google Play (android marketplace). There’s one more way to release your application which includes sending it directly to the users so that they can download it from your website or other available sources.

In this blog, I’m explaining step by step guide to publish your Android application on Google Play which is the world’s largest app marketplace. Check it out:

Step 1: I prefer performing Regression Tests before entering the marketplace.

Regression testing is an essential step to check whether your application is compatible on the all the devices you are targeting. So you need to test all the basic features of the app by running it on various devices and tablets.

Step 2: Application Rating- Well.. Is your app mature enough?

Google Play will show the maturity level of your application to the users. So you need to specify the rating of content in your app from available options as:

a). Low Maturity

b). High Maturity

c). Everyone

d). Medium Maturity

Step 3: Targeted Region- Most of my consumers are from London.

On Google Play, you can control your region or country to sell your application. So it’s your responsibility to precisely select the time zone, localisation or other specific demands according to the selected region.

Step 4: Size of the Application- Are you qualifying the minimum criteria?

Google has limited the maximum size for an APK to 50 MB for publishing it on Google Play. If the size of your application is more than 50 MB, or you want to avail a secondary download to your users, then you can leverage the APK expansion files. Google Play will freely host it on its infrastructure. And, it will automatically handle the download on devices.

Step 5: Screen Compatibility and Software Development Kit (SDK)- My app is not running smoothly on Tablets. What to do?

It is your responsibility to ensure that your application is designed to execute properly without any bug on the pre-specified Android platform versions. Also, it must support the screen size of the devices you are targeting.

Step 6: Pricing of the Application- Should I pay?

The price of the application must be decided prior because there are applications available on Google Play which are free and do not get affected by your application (your application should not get affected either). For this, you can do one thing i.e. to specify the price to a specific target country.

Step 7: Promotional Content- I’m the one you were looking for?

It is one of the broadly used market strategies to boost your product popularity among users. You can say a good practice to showcase the assets of product is a high-quality graphic. After publishing, the promotional content can be used for the store’s product detail page and is also shown in the search results of the brand.

Step 8: Upload release-ready APK file- Countdown begins..!!

In further steps, you will upload this APK file on the developer console. It is distributed to the audience. While preparing for the release of a product in the market, always try to configure, to build and a trial before the actual release of the application. To optimise your application, the configuration has to be done carefully. It includes basic codes, cleanup and code modification tasks etc. Build or debug process is done using Android SDK and JDK tools. The final step is all about testing, which includes the final check of the application, or you can say an assurance check before the application is launched in the market. When you have finished all these steps, then your application is ready for release and distribution in the marketplace.

Step 9: Wrap up the Application Detail- Who am I?

Google Play presents various options and tactics to promote your application. It encourages user-engagement on your main product page which shows details, colourful graphics, screenshots from your application and video content for introducing descriptions, backlinks to other apps and release summary. So, you can show an attractive and well-maintained application page with useful detailed descriptions.

Export Your Application:

There are few tools you must have access to export your application:

  • Dalvik Executables tools: Dx tool helps in converting .class file extension to .dex file.

  • Android assistance packaging tools: AAPT is helpful for converting a .dex file to .apk file extension.

  • Android Packaging Kit: APK is used for final stage deployment.

All you need is to export APK file before marking your presence in Google Play marketplace. For export, open your project in the Android Studio and click on ‘Build’. It will generate a signed APK. Now click on the generate signed APK displayed in the above screen and choose to create a new key store, it will store your application.

Write your key store path, key store password, alias and key password in the window. Click next. Once you are finished with filling all the information such as build type, flavours and destination of the app, click finish as it will generate an APK file for your application.

Google Play:

You need to register on the Google Play where you have to create a Google ID and accept terms and conditions. It will ask for a payment of $25 to proceed. Hooray..!! Once you are registered on Google play, you can finally upload your application.

Native Apps vs Hybrid Apps – Which Of These Offer Greater Advantages?

native apps vs hybrid apps

 

Total revenues from the global mobile app market is set to touch $190 billion by the end of this decade. For all the speculations over the growing maturity of this industry, the fact remains that mobile apps are still growing at exponential rates – and more & more new mobile technologies are coming into the picture. From a developer’s perspective, the options are pretty much clear – (s)he can create native (platform-specific) apps, hybrid (platform-agnostic) apps, or mobile-optimized, responsive websites which deliver most of an app’s utilities.

In 2015, native technologies were being exclusively used by around 20% of all app developers. Cut to 2017, and that figure had already fallen to below 3% – thanks to the rapidly proliferating popularity of hybrid applications. It can be reasonably estimated that, on average, 3-4 out of every 10 developers will start to work exclusively with hybrid technologies (giving up on native applications) within the next couple of years or so. In the following native apps vs hybrid apps debate, we focus on the respective advantages and probable issues of the two app development methodologies:

  1. Single platform vs multi-platform

    Native mobile apps are built for single mobile operating systems (iOS or Android). For separate mobile OSes, separate versions of the app have to be created. Native applications can typically access all the functionalities of a specific device, without any glitches. Hybrid apps, on the other hand, are created with standard code languages, and are meant to run on multiple operating systems. While plugins are available for hybrid apps, their customizations are not likely to be at par with native-built apps.

Note: Developers have to use Swift or Objective-C for iOS programming, and Java or Kotlin (in rarer cases) for Android development. For making hybrid apps, C# or Javascript (with HTML5) is commonly used.

  1. Frameworks and IDEs

    Depending on the precise type of app that has to be made, developers need to be familiar with the corresponding integrated development environments (IDEs), frameworks and platforms. Developers working on the Apple platform, for instance, need to have relevant experience of working with Xcode (latest version: Xcode 9.4.1) – while Android developers have to be conversant with all the functionalities of Android Studio (latest version: Android Studio 3.1.3). If you wish to make hybrid applications, however, a completely different type of expertise is required – with tools like Facebook’s React Native and Microsoft’s Xamarin. It might be a stretch to refer to the hybrid platforms as ‘tougher’ than the native IDEs – but they present a separate challenge for app-makers.

Note: Hybrid apps typically have a native shell that uses Webview to pull in the code (the shell can also be downloaded). The other important part of these apps is the back-end coding, done with Javascript or HTML5 or CSS.

  1. Are hybrid apps cheaper?

    To start off with, hybrid apps are generally less costly, and less time-consuming to build than pure native applications. However, there is a catch over here. The greater the degree of customizations implemented on a hybrid app, the higher the costs are likely to rise. In the long-run, native apps might end up being the more cost-effective propositions – thanks to the higher degrees of personalization options and the superior user-end experience (UX) they deliver. Let’s just put it this way – developers who have the biggest focus on quality should go with native apps, while those who wish to generate the maximum value in a limited time can opt to build hybrid applications.

Note: Hybrid mobile apps can also be viewed as a combination of responsive web apps and native applications.

  1. Preferences of end-users

    Delivering optimal user experience is the name of the game for any service provider at present. While native apps do have more natural design flows (and as such, are likely to provide better user-experiences), there is little to choose between them and hybrid applications in this context. In fact, all that final users look for is how well an app performs on his/her device, and whether or not it meets his/her expectations. Provided that the development has been done with due care and expertise, it does not make any difference to the user whether an app has been made with native or hybrid technologies. More often than not, it is pretty much impossible for a random smartphone-user to find whether an app is native or hybrid.

Note: The focus should squarely be on identifying the requirements of target users, and creating apps accordingly. Both native and hybrid apps can fit the bill, depending upon the situation.

  1. Development Cycle and Resource Usage

    Apart from being cost-saving propositions in the short-run, hybrid apps also have significantly shorter development cycles than fully native applications. Typically, native development requires higher amounts of manpower and technical resources as well. Since basic web technologies are used in a hybrid environment (like HTML or CSS), they are generally easier to build as well, than their native counterparts. A rather common strategy of many app developers is to go the native way for very simple apps, and consider using hybrid development frameworks (Xamarin, PhoneGap, Ionic, React Native, etc.) if and when that app becomes popular and has to be made available on other platforms.

Note: Native apps require separate coding to be done for each separate platform. Hybrid apps, on the other hand, are made on the ‘write once,run anywhere’ principle.

  1. Performance factor

    In terms of speed and micro-level performance metrics, native apps still hold all the aces, by virtue of their more customized designs. While hybrid applications are becoming more and more user-friendly over time, they are still some way off from matching the speed and performance of completely native apps. In addition, developers can rest assured of full access to native APIs (application programming interfaces) for native apps. The degree of API access for hybrid apps is lower. Since hybrid apps need to record web technologies for optimal performance, they do not quite deliver that ‘right feel’ – something that is the USP of native apps.

Note: The functionality of hybrid applications can run into problems if high-level device interactions are required. There is a limit to what native plugins (which manage such device interactions) can achieve.

  1. The learning curve

    While it would be an exercise in futility to find whether native IDEs or hybrid frameworks are ‘easier to learn’ – it can be stated that the learning curve for hybrid app development is comparatively less steep. Once a developer gets the proper hang of a framework (say, React Native), (s)he can start making apps for multiple mobile operating systems. Native app development, however, requires full proficiency with the tools and techniques of each platform. That typically takes considerably more time. Not surprisingly, the time to market for native apps is, on average, quite a bit higher than that of hybrid apps. From the earnings perspective though, native apps offer separate financing streams for the different platforms. All the ROI from hybrid apps is channelized through a single stream.

Note: Development of both hybrid and native applications requires stable internet connections – although this requirement is greater for the former. In a native scenario, internet is required for the API-client applications and for updating a particular app.

  1. Overdependence on plugins and libraries

    This is something that holds hybrid apps back somewhat. These apps are heavily dependent on external frameworks (Ionic, Cordova) as well as on native plugins. The more plugins are added, the more complex the overall development process becomes. It might also happen that a particular framework/library version is not in sync with the platform – and performance glitches can crop up as a direct result. Native apps have no such dependencies, and hence, they offer a more consistent performance assurance. The availability of native SDKs is a big factor in this regard.

Note: For high-end gaming applications (3D/HD) that require heavy graphics, native development is the correct approach. Hybrid technologies might not be able to handle intensive animations rendering and other performance requirements satisfactorily.

  1. The security factor

    Well over 22000 malicious mobile applications get blocked everyday. There are multiple channels via which both native apps and hybrid apps can come under attack – right from code injections and poor implementation of SSL, to data leakes, problems in data storage and reverse engineering. However, hybrid applications do have an extra risk layer – since they have external tools and frameworks for coding. Also, the developer ecosystem for native mobile applications is still much stronger than that of hybrid or web apps. Irrespective of whether separate app codes are maintained (native) or platform-agnostic single code base is used (hybrid), developers have to keep an eye out for probable security threats and manage them effectively.

Note: In a recent survey, it was found that, when faced with adverse app experiences, 48% users were likely to reduce its usage, while a bad word-of-mouth publicity might be started by 31% of them. It’s all about ensuring that final customers are not put off by any feature or shortcoming of an app.

     10. Web technology vs specific technology

The entire native apps vs hybrid apps debate boils down to this. While specific technology is used in native applications (Swift for iOS apps; Java for Android apps), web technology (CSS, Javascript, HTML) lies at the heart of hybrid mobile apps. It also has to be kept in mind that all hybrid apps run in WebView – which can cause certain performance issues as well, if there are any problems with widgets. In terms of performance acceleration capabilities based on the underlying hardware, both types of apps are more or less at par.

Note: Native apps are usually fully compatible with other applications installed on a device. Compatibility issues are more likely to crop up in the case of hybrid applications.

     11. Updating an app

This process is decidedly simpler and quicker, when we are talking about hybrid applications. Everybody does not set up their phone apps to be auto-updated when connected to wifi. Changes made in a native app are reflected ONLY after a user updates the app from the store – and repeated reminders for updation can end up irritating customers. In the hybrid development scenario, it is not necessary to update the apps in the stores. Modifications made on app pages that are loaded directly from the server get displayed immediately. In a nutshell, hybrid app updates generally do not require any additional human involvement, while native app updates can result in unnecessary (and negative) attentions.

Note: The fact that a single source code is used for hybrid apps also makes it easier for coders to make changes in their programs with ease. In most cases though, hybrid apps do not support offline mode.

     12. Companies love Native AND Hybrid apps

In 2012, Facebook CEO Mark Zuckerberg admitted that his company’s mobile strategy was a bit ‘too reliant on HTML5’ – and switched over to native applications. Native-built apps are also used by several other industry biggies, like Instagram, LinkedIn and Redfin. The love for hybrid applications is also increasing – and they are already being used by organisations like Banana Republic, OKCupid, Untappd and HealthTab. The tradeoff here is pretty much apparent – companies that wish to deliver the most optimal mobile experience are sticking with native apps, while those that wish to reach out to the widest possible audience quickly are taking the hybrid approach.

Note: Hybrid apps can also be operated as Progressive Web Apps, or PWA.

Native apps and hybrid apps both have their own advantages and probable downsides, as is evident from our discussion above. At the end of the day, the onus is on the developers to consider their budget, how quickly they need the app, the maximum level of complexity, and the degree of UX optimization required – and then determine whether a native or hybrid strategy would be the best way to go forward. The final choice should depend, not on the technologies per se, but on what you want an app to do – and how such features can be added in the best possible manner.

 

 

NB-IoT In India: Looking At The Key Facts, Stats & Updates

NB-IoT in India: Trends and updates

 

India is fast growing into a strong global IoT hub. By the end of 2016, there were ~200 million ‘connected devices‘ in the country – and this count has been estimated to jump to 2.6 billion units in 2020. In terms of revenue, we are looking at an almost 3X increase over the 2016-2020 period ($5.6 billion vs $15 billion). Globally, the overall size of the IoT market will swell to well over $3 trillion by the end of this decade. LPWAN (low power, wide area networks) standards are driving the growth of IoT across the globe in a big way. According to a recent Infoholic Research report, the worldwide LPWAN market will be growing at a CAGR of >93% between 2016 and 2022. We have already highlighted the importance of Semtech Corporation’s LoRa technology in previous posts here and here. Let us now turn our attentions to another competing, and increasingly popular, technology – Narrowband IoT, or NB-IoT.

There are, at present, around 200 million active NB-IoT connections in the world. Come 2021, the number of connections will shoot up to 685 million (a 242.5% spike). The 2017-2022 CAGR of the global NB-IoT market will be ~62% – going up from $16 million (2017) to $181 million (2022). While Europe and North America are, rather expectedly, the early pace-setters in this domain – the Asia-Pacific has emerged as the biggest contributor to the global NB-IoT market – thanks to the proliferation of smart cities, and the large-scale deployments of optimized IoT solutions. The growth of NB-IoT in India over the past few quarters has been well and truly remarkable too. Reliance Jio, in collaboration with Samsung, is planning to deploy a pan-India cellular IoT network (covering 99% of the nation’s population). Last month, Vodafone reported that it is deliberating on the implementation of NB-IoT solutions in India (following its ‘superIoT’ approach). Over here, we will briefly touch upon some interesting facts and stats about the growth of NB-IoT in India:

  1. What exactly is NB-IoT?

    Before getting down to analyzing the technology, it is important to understand the precise nature of narrowband-IoT. Broadly speaking, NB-IoT refers to a new form of LPWAN radio technology, that is typically meant for transferring low data volumes over large networks (NB-IoT powered devices can be used for indoor as well as outdoor use). Alternatively known as LTE-M2, the technology is implemented either through dedicated LTE base stations, or on 200-khZ bands that were not previously in use. NB-IoT was standardized by 3GPP in September 2015 – with the LTE Advanced Pro Release 13 specifying its standards. An optimally functioning NB-IoT setup can deliver a maximum range of 34-35 km (significantly higher than that of LoRa; comparable with GSM), while the downlink data rate varies in the 2 – 170 kbps range. Unlike LoRaWAN and Sigfox, NB-IoT uses licensed LTE frequency spectrums. The highest possible uplink data rate is 250kbps, and the maximum coupling loss is 164 dB (marginally higher than LoRa; similar to Sigfox).

Note: Apart from the ease of bandwidth availability, NB-IoT ensures minimal interferences, excellent battery performance, and general ease of usage. It is, hence, an ideal communication protocol for sending/receiving data over long distances.

  1. Sectors under the NB-IoT focus

    Enterprise applications are increasing in importance in India – and smart automation is playing a key role over here (think: Smart Cities Mission, Digital India). Vodafone, which is actively involved in NB-IoT implementations for business/enterprise cases in Europe, has similar plans for the Indian market in the foreseeable future. The telecom giant is eyeing four industry verticals – education, automotive, medical and energy – as the ones with the biggest growth potentials for IoT. In addition, the consumer IoT sub-domain is growing fast too – thanks to the availability and growing awareness about smart home applications, tracking tools, and smart asset management solutions. The prime point of concern in the Indian IoT market is gradually shifting from ‘connectivity’ to ‘security’ – thereby entering a phase of early maturity. NB-IoT promises to be exciting on two counts – it can help individual end-users, as well as automate enterprise applications to take them to the next level.

Note: Since 5G will have significantly lower latency levels and bring up opportunities for AR/VR tools – it will make IoT connectivity in general, and NB-IoT use cases in particular, stronger.

  1. NB-IoT overcomes bandwidth limitations in India

    For all the developments of LoRa technology in India, the fact remains that there are restrictions on unlicensed IoT bands in the Indian market. NB-IoT does away with this issue, by using licensed frequency bands (the license fees are low). Availability of NB-IoT modules is hardly a factor – since the technology is making a relatively late entry over here, and multiple MNOs (mobile network operators) are already offering such modules. The onus lies on IoT developers to factor in the bandwidth requirements and the limited mobility of narrowband-IoT, while using the technology to create new applications/tools. Competitive pricing is yet another must-have factor for any new technology to be practically viable – and NB-IoT comes up trumps regarding that. The average per-device monthly cost should be around $0.5 (or even slightly lower, depending upon the precise nature of applications). The growth of NB-IoT in India will also be fueled by the network coverage capabilities of the technology.

Note: The value of the Indian digital economy will touch the $1 trillion mark in 2024. It can safely be stated that the country is well on its way towards becoming a ‘digital superpower’.

  1. The developments at MWC 2018

    The Reliance Jio-Samsung partnership is important for the large-scale commercial deployment of NB-IoT in India. At this year’s Mobile World Congress (Feb 26 – Mar 1), several other interesting NB-IoT-related announcements and developments also took place. For starters, France-based Sequans Communication released its first-ever ‘made for NB-IoT’ chip. A new set of 9 radio frequency (RF) chips for LPWANs were showcased by Qorvo. Using Vodafone as the network for its live demo session, Chinese chip vendor company Goodix announced the start of NB-IoT chip sales (the IP will be obtained from CommSolid GmbH). A dual-mode network (LTE-M1/NB-IoT) was presented by Vancouver-based startup Riot Micro. It was also announced at MWC 2018 by China Mobile that chips from 5 companies – ZTE, Huawei, Qualcomm, Mediatek and RDA – have been used to deploy full-fledged NB-IoT networks in as many as 346 cities. According to Qorvo, the global LPWAN market grew by an impressive 20% in 2017 – and by the time 2025 rolls in, it will be the single largest connectivity technology in the globe (with 4 billion+ active IoT devices).

Note: Just as the non-cellular IoT market is being led by LoRa (with Sigfox also having a strong presence), NB-IoT leads the cellular IoT sector.

  1. Successful NB-IoT trial runs in India

    Tata Communications has plans to deploy the largest LoRaWAN network in the world in India. The project, spanning 38 cities, will be completed before the end of 2019. NB-IoT networks are also set to become commercially available on a large-scale in India – with Reliance Jio (and Samsung) and Vodafone both eyeing rollouts in the coming months. Vodafone India announced last month that it had already completed multiple smart city test cases in Pune and Kolkata. At present, more use cases from different business sectors – from retail and automobiles, to manufacturing and healthcare – are being researched. On its part, Reliance has already deployed a fully functional NB-IoT network in Mumbai, and the networks in several other cities are being planned. The total number of Jio subscribers is already well over 158 million, ~9000 new towers are being set up every month, and LTE coverage in India is estimated to reach 99% by 2018 Q4.

Note: In North America and Europe, Deutsche Telekom leads the way in terms of NB-IoT network deployments.

  1. Disruptions with NB-IoT

    The chief objective of the Reliance Jio-Samsung collaboration is the assurance of faster, interruption-free internet across India. Non-IP data delivery will be something that will set apart the NB-IoT movement in India apart – and this innovation will be backed by a steadily growing user-base. For the deployment, all the installed Jio stations will have to be upgraded (the spectrum finalization will also pave the way for 5G, as and when the technology comes along). According to reports, narrowband-IoT can bring about technical disruptions in various industries – like transportation and logistics, smart metering utilities, weather tracking and vehicle tracking, security & surveillance, and predictive maintenance. In a country like India, NB-IoT is likely to pay a prominent role in smart agriculture/precision farming as well – improving yields and efficiency levels, and lowering uncertainties. As already mentioned above, the technology has the power to revolutionize both enterprise and customer IoT systems.

Note: The IoT scaling opportunities in India are unmatched (according to Qualcomm). In 2016, Qualcomm entered into a partnership with Philips, and another collaboration with CISCO (in Jaipur). The market is growing fast.

  1. Help from Finnish NB-IoT technologies?

    In March, Telia became the first Finnish operator to implement NB-IoT technology in its network. In general, Finland is easily one of the global leaders in NB-IoT applications – with Nextfour (in partnership with telecom giant DNA) launching a LTE-M/NB-IoT application in Turku. Not surprisingly, Finnish NB-IoT technologies are being used as a reference point for Indian companies. Late last month, it came to news that a leading telecom service provider in India has expressed interest in the IoT technologies that are being used in Finland – for the optimization and betterment of the Indian IoT sector. Both Reliance Jio and Bharti Airtel have plans to penetrate the IoT and home automation market – with the help of powerful and innovative M2M solutions. Given that the domestic home automation market is set to move beyond $54 billion in 2022, there is ample scope for more players to use NB-IoT to make a difference in this sector.

Note: Reduction in costs, efficiency boosts, better reliability and easy deployment options are some of the main advantages of NB-IoT.

  1. Band selection for NB-IoT

    The 865-867 MHz unlicensed spectrum band is used for deploying the LoRaWAN protocol in India. Given the top-notch coverage of NB-IoT, the 900 MHz band (licensed) is generally used by most mobile operators for it (the 700 MHz and 800 MHz bands can be used as well). By 2015, there were already 14 commercial networks operating on the MHz band – where indoor penetration levels are excellent, there is high propagation, and the existing ecosystem is also fairly strong. Interestingly though, 1800 MHz is the frequency band that has the highest percentage of active LTE networks (>76%) in the world. In countries like Australia, Singapore, China and the United Kingdom, the 1800 MHz band is the most popular for LTE networks. The 2.1 G and 2.6 G bands are also used, albeit at a much lower level. Developers need to be aware of the country-specific bandwidth regulations, and abide by the same – while designing with NB-IoT.

Note: NB-IoT cells are typically larger in size than standard MBB cells. The former should ideally be able to accomodate ~100 concurrent connections.

  1. Main features of NB-IoT

    The buzz about IoT applications in general, and NB-IoT technology in particular, is rising in India. A lot of factors are serving as the drivers of this 3GPP-standardized  technology – right from the 600 bps-250 kbps bidirectional transmissions and the ~10 years battery life (using two AA batteries), to the relatively easy maintenance requirements, the SIM-based security system with ciphering and authentication, and the easy plug-and-play usability (no local networks/gateways required). Compared to GPRS, NB-IoT can deliver a much higher (almost 20 dB) coverage. The fact that NB-Iot works only on licensed bands adds an extra layer of security to the technology. The minimum number of connections in a single NB-IoT cell is 50 – and the real-time data tracking is high on accuracy. What’s more, connectivity and modem costs are minimal – and that, in turn, means that the IoT communication costs with NB-IoT can be significantly lower than that associated with LoRa or 3G modules.

Note: Mass deployment of IoT applications can go a long way in improving public health and safety standards. Users would also be able to save a lot of time and energy by switching over to LPWAN technologies.

       10. NB-IoT: A major source of revenue

Investing big on a new communication technology would only make sense if the returns are high enough. NB-IoT is on firm grounds regarding this – with a cumulative revenue of $1.67 billion being projected for the 2016-2021 period. Smart city projects, smart home applications, and automotive and logistics tools are going to be the top-three revenue earners (in that order). Safety & security ($227 million) and smart agriculture ($159 million) are two other sectors that are going to be disrupted by the arrival of NB-IoT, both worldwide and in India. The cost advantage of NB-IoT is also worth a special mention. The average price of a LoRa module and a Sigfox module is $8 and $9 respectively – higher than the average cost of a NB-IoT module ($5). To put things in perspective, a full-featured Cat4 module can cost as much as $30. The tremendous revenue opportunities of NB-IoT, together with the lowly cost figures (only Bluetooth is cheaper) indicate that large-scale deployments can be really profitable for operators.

Note: LPWAN use cases can broadly be classified under 4 different categories – Industry, Appliances, Personal and Public.

       11. Is NB-IoT suitable for everything?

As both Reliance Jio and Vodafone have pointed out, narrowband-IoT can be deployed in many different business sectors – and more and more new use cases are coming into the picture. That said, the technology might not be an ideal fit in certain cases. For example, since cellular networks do not generally have strong power-saving mechanisms, they are not particularly great for applications that involve infrequent transfer of very small amounts of data. Utilization of capabilities is yet another factor – since NB-IoT does not require voice technology, or high data transmission rates, or messaging tools, all of which are present in standard 3G/LTE devices. As a result of this, the effective cost of using devices only for NB-IoT goes up. Also, the operability of NB-IoT can become rather suspect in remote locations (in the absence of base stations nearby). In such scenarios, the battery life gets adversely affected as a result of the extra strain on the device transmitter. The good thing is, operators are doing their best to work around these issues – and make sure that NB-IoT standards have uniform usability.

Note: There are three alternative deployment scenarios for NB-IoT – standalone (with new bandwidth), guard band (with reserved bandwidth) and in-band (with same resource in LTE carrier).

      12. Understanding the developer mindset

In 2015, there were 4.5 million IoT developers in the world. Cut to 2020, and this figure will cross the 10 million mark – with many Indian players joining the community. The burgeoning popularity of NB-IoT has a lot to do with what these developers actually want from their IoT communication systems. According to a M2M Barometer Survey report, ‘2-way communication’ (55%) and ‘low cost’ (43%) are the two most sought-after features in any IoT technology, followed by ‘extended geographic coverage’ (40%) and ‘long battery life’ (34%). Now, NB-IoT satisfies all of these requirements and many more – and that makes it easier for developers to adopt it and deploy it in their LPWAN systems. By the end of 2024, 6 out of every 10 IoT devices will be powered by NB-IoT – emphasizing the importance of the technology in the long-run.

Note: In January, Telstra became the first Australian carrier to deploy NB-IoT in its network. Incidentally, Telstra also provides Cat M1 IoT coverage (started in 2017).

Apart from the endeavors of Reliance Jio and Vodafone, Huawei is also deliberating with leading Indian telecom players for commercial IoT deployment. There are potential interoperability issues between Huawei and Ericsson (which can affect the rollout of NB-IoT globally). However, the successful ‘interoperability tests’ done by Vodafone reduce such concerns somewhat.

Under the ‘Smart Cities Mission’ of the present government, 100 smart cities will be developed in India. In a truly ‘smart city’, narrowband-IoT can be utilized for a lot of purposes – like smart water metering, air-quality monitoring, smart parking, damage prediction, sheep tracking (in farming), and smart waste management. All of these (and much more) are already being done in different countries. With LoRa and NB-IoT both set to become mainstream in India – the country can easily rank among the global LPWAN leaders in the not-too-distant future.