As 2020 drew to a close and 2021 set in, conversation spaces were abuzz with predictions, theories and trends about what was to follow. The industry of software development in Sri Lanka was instrumental in shaping the opinions of numerous tech enthusiasts, as customer-centric applications were being developed in record time, with the assistance of cloud support services. A leading software offshoring destination for discerning international markets, Sri Lanka has long since made its mark in the application development arena. But what else is in store when it comes to delivering applications that go beyond their current benchmarks?
Although the technology industry at large is constantly evolving, the circumstances surrounding 2020 spearheaded drastic changes across the digital landscape. One on end, these circumstances had to do with prevailing health and economic situations. On the other end – the routine rise of numerous technology trends themselves. As the pandemic was unfolding, priorities were naturally shifted to accommodate business continuity in the wake of lockdowns and social distancing. Albeit being far from resuming normalcy, the gaze now seems to be gradually shifting towards how ‘the new normal’ can be sustained with up and coming technologies.
In other words, incorporating fresh trends such as 5G to current use cases is a topic worthy of discussion. This is where IoT comes in. While the Internet-of-Things had been steadily gaining momentum well before any pandemic ever took place, its range of applications have expanded across industries, geographies and market sizes. Now, it’s not just subject to Alexa alone; use cases range far and wide, with many devices barely even recognizable as being IoT.
Such IoT proliferation is on the rise, no doubt. But which trends are being created by devices turning ‘smart’, thanks to other corresponding technologies such as AI and machine learning? Here, we explore a few such trends. While this isn’t an exhaustive list by any means, it will also serve as a great focal point for other technologies such as edge computing – since today’s technologies are all entwined with one another.
The manufacturing industry was one of the first to implement IoT technologies in its factories and assembly lines, when it came to large-scale commercial use. With other use cases also developing outside of the manufacturing industry, this trend was slowly shifting gears. Voice assistant devices and smart watches were some of the more popular trends which were starting to take consumers by storm.
IoT for healthcare.
The pandemic further propelled IoT to be used elsewhere, particularly in healthcare. Telemedicine already had a market, with boutique applications allowing users to consult doctors from the comfort of their smartphones. This was particularly popular in the psychotherapy sphere, as users now had the option to consult therapists who would’ve otherwise been out of reach due to a lack of physical proximity. Telemedicine established a stronger foothold, however, as lockdowns forced the masses to forgo their regular healthcare needs, such as check-ups, diagnosis of ailments and testing. This is where IoT technology really skyrocketed, as home-based wearable technologies were now adopted to proactively monitor vital signs by healthcare professionals remotely. Even equipment such as oxygen pumps and wheelchairs were fitted with IoT technology, to also be monitored for smooth function – and alert accordingly should any inconsistencies be found, for treatment well ahead of time.
IoT for retail.
Moving on to retail, customer experience was also a matter of importance well before a global pandemic set in. But swiftly adapting to escalating requests was absolutely crucial (albeit highly challenging) – especially since many otherwise notable companies were losing their customers’ trust due a lack thereof. Customer experience has long since been an area which has depended on advancements such as AI and machine learning to offer a deeper understanding of customers’ psyches, but pandemic-induced lockdowns took this to a whole new level.
As customer support agents were forced to work remotely while trying to sift through ever-growing piles of customer requests, chatbots/virtual assistants/auto-receptionists were a ‘lifesaver’. As chatbots undertook common and/or minor requests, work was rapidly streamlined for agents since only complex inquiries had to now be attended by them. Nonetheless, the data gathered via chatbot interactions was a boon for other business units such as warehousing/inventory, as the IoT equipment functioning in these areas could now be tailored for operation based on the insights gathered.
Cloud computing has been paramount in serving (and saving) businesses during a crisis – and what we all experienced in 2020 was also no exception to this rule. As reliable as the cloud has been, it still comes with certain caveats that could prove disadvantageous in certain contexts. This isn’t to say that the cloud will be rendered obsolete – this couldn’t be further from the truth, in fact. Whether you are sourcing your cloud computing needs directly from a leading provider, or via your IT agency which may be an AWS partner, for example, being mindful of how you can further elevate what hosted solutions are already providing to your business is a worthwhile topic to consider.
This is where edge computing can be introduced into the picture, as it can help strike the right balance with a more hybridized approach towards data management and output. In a nutshell, edge computing presents the capability to process data within local servers or within IoT devices themselves, thereby eliminating the need to transfer data across long distances towards a centralized management system. For the customer-focused business, fast turnarounds imply profits. Depending on industry or expertise, fast turnarounds may also make all the difference between life and death (healthcare, law enforcement and rescue services are some examples).
Transferring data to and from a centralized system can present latency – something which can be eliminated via edge computing. Although network size may increase due to this (since data will now be stored across multiple locations), security can still be maintained on an endpoint level. In turn, this helps minimize the repercussions of a possible threat, since data will be scattered across multiple servers – as opposed to one major centralized system.
Localized servers can also cater to local tastes. In other words, regional servers can offer fast and efficient services to local markets, that too at a reasonable price. Cost efficiency applies to both businesses and consumers; as businesses are able to cut down on costs, products and services offered can also be made more affordable overall. In a business world that is increasingly oriented towards customers, data or ideally a combination of both, IoT devices powered by edge computing are bound to be powerhouses for delivering fast yet intelligent solutions – all while functioning independently and with little to no manual intervention.
The IoT technology is formed on the basis of making devices ‘smart’. But without data, this concept is futile. This means that data is necessary to fuel IoT devices into capturing, processing and delivering data that generates valuable yet timely actions. With actions and deliverables come more data, and the cycle repeats again. Once more, the field of data isn’t newfound either; just like telemedicine and edge computing, data has long since been crowned king of the digital world.
However, the increased use of IoT has brought the topic of data (especially big data) into the limelight, since smart devices are reliant on data for functioning and performing. In turn, this also ends up emphasizing on the importance of gathering data in an organized yet secure manner – a reminder that’s especially important for companies who are still not at the forefront of doing the very same. Add to this other technologies that are subsequently required to also churn this data for actionable insights; from AI-infused application development to sophisticated business intelligence, the right ammunition is essential for robust data analytics.
As use cases for IoT increase across industries, specialties, geographies and business volumes, your existing big data shall also see an equal increase in how it is queried for insights – another trend that has the potential to gain momentum, come 2021.
Although primarily focused on by larger technology giants such as Microsoft and IBM, digital twins have also been mainly involved in the manufacturing industry. For those who aren’t familiar, a digital twin is a virtual replica of a physical asset. This digital twin is also capable of emulating the functionalities of its real-life version, thereby giving companies the chance to test future products/upgrades with minimum downtime and maximum productivity.
By simulating the functions of an actual physical product, it is pretty clear to see how IoT devices can contribute to such a process. Data gathered by smart devices is crucial here, as this can be utilized to close the loop between cause and effect; generate a virtual replica and observe how it reacts to the elements, in other words. Conducting thorough testing without having to create physical prototypes may be one of the biggest benefits of digital twins, as it can save companies a lot of money, time, effort and raw materials.
Add to this the fact that only corporations which manufacture large-scale machinery are involved in applying digital twins; from assembly lines to buildings, creating physical prototypes for such structures is a long, tedious and exorbitant process, needless to say. Even if a single variable changes, a digital twin can instantly deliver real-time results to indicate what can be expected, so that actual physical deliverables are honed to near-perfection from the very first version itself. The data gathered by IoT devices will play an instrumental role for all this trial-and-error.
But what really differentiates digital twin technology that’s powered by IoT is the fact that tangible outcomes can be instantaneously gathered, through data which also hails from real-life scenarios. In the long-term, this can also turn into a historical blueprint for future specialists who join the trade, as forthcoming advancements can be made based on what transpired earlier. This will also assist future specialists in the training process, since the tips and tricks of master specialists can be preserved within digital twins.
Technology in general has facilitated everything that our world relies on, in the wake of a global pandemic. IoT specifically has been an important component here, as social distancing compelled millions to stay at home and continue their way of life by relying on the smart devices around them. Such smart devices also extended to a commercial level; from hospitals to logistics, IoT devices were sprouting everywhere to maintain normal working operations by gathering data and delivering actionable outcomes.
From telemedicine to chatbots, applications now range far and beyond what was mainly seen in factories and assembly lines. This has also given data (an otherwise highly integral component in our digital landscape today) even more importance, since IoT devices are bound to challenge data-based outcomes in myriad ways. But testing the limits isn’t just subject to data – even cloud computing is another crucial component that needs to be redefined in the wake of maintaining a business which is oriented towards sophisticated IoT devices.
Edge computing is another technology that is bound to follow suit, since it isn’t just local servers that can fulfil the duties of a centralized database in the cloud – even IoT devices now bear the potential to be built with capabilities that are advanced enough to process data within the device itself. This invites advantages such as reduced latency and cost-effectiveness, thereby giving businesses the leverage they need especially for long-distance markets.
Last but not the least, digital twins have been a virtual structure of choice for numerous reasons. Ranging from real-time results to the omission of physical prototypes, digital twins can significantly benefit from data that’s fed in via IoT devices stationed in real-life environments.
As a result, there’s plenty to look forward to in the world of IoT – and chances are that we may just get to see many such trends unfold, in 2021.
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