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Marching Towards An AI-Enabled IoT Future

The Internet of Things (IoT) has been a buzzword in recent years, given its role in shaping smart cities and consumer lifestyle across Asia Pacific. According to IDC, the region seen as the frontline for IoT adoption will account for 8.6 billion of 29.5 billion connected devices globally by 2020. Industries are increasingly realising how IoT can accelerate digital transformation in organisations, enhance data connectivity and exchange across the network, and provide new opportunities for virtual and physical systems to become more integrated. Across the region, companies have been applying contemporary data science techniques to deliver applications, products and services through smartphones. The combination of IoT, Artificial Intelligence (AI), machine learning and predictive analytics is currently creating big economic value for organisations across the region.

More than ever, a world in which sensors and intelligence are tightly coupled together, instead of being separate, is now considered the de facto standard. Today, personal assistants backed by AI and machine learning are redefining the smart home experience enhancing interconnectivity between home appliances, sensors and the internet. For instance, IoT sensors on the refrigerator enable a smart assistant to determine when to place an order with the nearest supermarket once it detects that the fridge is out of grocery items. Supermarkets, in turn, provide drones to streamline the home delivery of orders.

Beyond the smart home, various sectors have also been betting on the combined power of IoT and AI to deliver competitive advantage.  Healthcare institutions today are increasingly adopting technology that offer diverse remote monitoring, healthcare delivery, and in-home diagnostics capabilities, which leverage both IoT and AI. Smart healthcare systems today, for instance, incorporate round-the-clock real-time data streaming, medication reminders and real-time medical diagnosis, all of which reduce the need for hospital visits.

Today, IoT and intelligence have become interdependent alongside the maturity of digital use cases across the region – and the edge is playing a big part in this new model.

Deploying IoT on the edge:  A smart business move for enterprises

Generally, the maturity of digital use cases necessitates enhanced intelligence. As more intelligence is added to digital processes that are supported by data derived from real-time production processes, the dependency on connectivity to the cloud becomes a liability. With production required to continue in spite of disruptions in internet connection, enterprises have seen the value of deploying fully functional IoT platforms on the edge – including advanced analytical processing capabilities like complex event processing, which were previously available in a cloud-only fashion.

AI and other analytical tools, such as machine learning and time series analysis, need copious amounts of data. However, moving all this data into the cloud is a costly solution, especially if the data is generated in remote areas. The edge is seen as desirable when there is a need to minimise solution latency, data traffic and data storage in the cloud as it helps aggregate and pre-process data for centralised enterprise-wide solutions. This means that analytical tools are close to the source, with only the necessary data transferred to the cloud for enhanced insights. However, machine learning is contingent on the availability of example data in abundance and this is where scalability figures into the equation.

Deriving value from IoT and AI: The build-or-buy question

According to McKinsey, a sustainable platform for creating and managing applications, running analytics and storing and securing data allows organisations to derive more value from IoT.

While incorporating AI into IoT is definitely a smart business move for enterprises, building such a platform on one’s own is quite difficult as IT teams might not have the skills, tools and sufficient domain expertise to integrate systems and scale properly.

In light of this, IT teams need to ask themselves if they will be able to meet security requirements and adapt to future IoT sensors and networking complexity before taking on IoT projects on their own. More often than not, enterprises build their own IoT platforms and experience “builder’s remorse” afterwards due to mounting platform building and maintenance costs. Additionally, the effort required to provide business units with the desired IoT platform functionality is oftentimes beyond what is expected, with balancing platform integration requirements becoming a key challenge for organisations.

Assumptions around anticipated IoT deployments provide insights that allow enterprises to decide whether to build or buy IoT platforms. MachNation has recently developed an IoT platform build-or-buy total cost of ownership (TCO) calculator, to ease the decision-making process for enterprises based on certain factors. These include the number of IoT devices, type of IoT devices, and even annual inflation rate. Enterprises should likewise consider the percentage of edge processing capabilities used by IoT devices, whether the IoT platform has either device management or data management capabilities, and whether the IoT platform supports single or multiple IoT applications over five years.

The edge as the new standard

As IoT and intelligence become more intertwined, enterprises are slowly realising the need for flexible platforms that support scalability and new data types. Edge computing is now becoming the norm, rather than the exception, as intelligence moves to the edge.

However, as with any new digital transformation implementation, deploying IoT on the edge is not without its challenges. This is where enterprises should seek to implement an agile approach in change management, with leaders stepping in and communicating how this can benefit employees across different levels. Only then can enterprises fully optimise machine learning and better leverage insights from IoT data to create more value within their organisations. – Network Asia

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