Edge Computing: Where AI meets the Internet-of-Things

Srinivas Rao, Sr. Director, System Engineering, Dell Technologies

By Srinivas Rao, Sr. Director, System Engineering, Dell Technologies

The market dynamics have evolved rapidly over the past few months owing to the circumstances created by the pandemic. There is no denying that businesses have started their digital transformation journeys, however, the explosive growth and increased utilisation of connected devices have resulted in unprecedented volumes of data. Moreover, this volume will continue to grow with the adoption of AI and IoT devices as well as with the coming up of 5G networks.

At the same time, emerging data-driven technologies like the Internet-of-Things (IoT), Artificial Intelligence (AI), Augmented and Virtual Reality (AR/VR) and Blockchain are dominating many conversations in the technology landscape. Organisations mapping out their digital transformation journeys are currently trying to understand how these emerging technologies fit into their strategies. 

One important consideration for these technologies is where they overlap or can be used in conjunction to achieve business outcomes. For example, where AI meets IoT, sometimes referred to as the Artificial Intelligence of Things (AIoT), provides for capabilities beyond the individual adoption of either technology. AIoT delivers an avenue for networks of connected devices to gather vast amounts of data from the physical world, and with programmable intelligence, learn to reason and process this data into information and insights, then act on it the way humans do. 

The link between the physical and digital world

The intersection point of the physical and digital worlds is what I call the ‘Edge’. It is the point where data is generated, gathered, and processed to create new value. The Edge presents new challenges to the way the IT industry approaches computing. Where there earlier was a sense of reliance on traditional data centers and cloud computing to process data generated outside of data centers, there is now a need to derive real time value at the point of generation necessitates the presence of computing resources at the Edge. This has led to the emergence of Edge Computing. 

Edge Computing drives value for organisations by accelerating both the discovery of insights from data and the digitisation of key business processes. It also allows businesses to redefine their end customer’s experiences.

An interesting consequence of Edge Computing as it pertains to the Artificial Intelligence of Things, is that it becomes the vehicle which brings intelligence (AI) closer to the source of data generation (interconnected things). In the new age of Edge computing, compute platforms at the Edge will provide lightweight designs that can be successfully deployed despite spatial, environmental, power and connectivity constraints. These designs can be secured and can support applications that require insights at the speed of real time and in the near future, organisational strategies for Edge can be expected to differ greatly with no two deployments being the same. 

Defining Edge and its impact 

Defining the Edge in terms of business outcomes will bring a level of clarity. For example, wind farmers who need to monitor the health of windmills will define Edge much differently than the dairy farmer who wants to monitor the health of their cows.  Even though the use case is similar, subtle differences around ‘what’ is being monitored will affect how the technology deployments will occur; down to data architectures, platform of choice, data processing and security at the Edge.  As with most adoptions of new technology, deploying at the Edge should have measurable milestones and quick wins on the journey to success.

Hence, organisations need solutions, which will support their entire data lifecycle management via consistent ecosystems that scale at the Edge and span on-prem and off-prem clouds. This is extremely crucial while keeping in mind the costs that are incurred when capturing, analysing and extracting value from untapped data sources. They will also need solutions that are built to meet the demands of operational and physical constraints that define their ‘Edge.’  

To conclude, the Edge is now being reinvented with technologies like AI, IoT, and 5G, which brings added value to business outcomes. Harnessing the value of data with edge computing will not only reduce workloads, but at the same time can optimise their networks and services to offer flexible offerings to customers. And as we move ahead in the new data era, the dependence on internet- connected devices will be increasing day by day, hence making edge a master-stroke for businesses to excel ahead in this competitive environment.


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