Innovating on the Edge

Innovating on the Edge

FountainBlue’s March 12 VIP Roundtable on the ‘Innovating on the Edge’ topic included executives representing a wide breadth of backgrounds and perspectives. We began with some definitions about the ‘Edge’. In the ‘old days’, the Edge might be defined by where the wires end – at the point of going wireless. But today, most things are not hard-wired, and we look more at the edge of the cloud – where the cloud meets the sensors and devices.Our executives agree that it’s becoming increasingly more important to innovate and manage on the edge, but there are many business and logistical challenges for doing this well. 

• Data Challenges: The volume of data generated by devices on the edge is immense and the challenges are varied.
• Relevancy: getting filtered and relevant data to the right reports and programs
• Latency: the time it takes to get the data to the right report and programs
• Movement: moving data from the edge to other areas in the network and in the cloud can be complicated and takes time
• Storage: management and maintenance of current and past data can be complicated and expensive

Problems beyond the data include:

• Computational Issues: programs processing of the volumes of data to understand what’s relevant, what the implications are
• Outdated and Sub-optimal Programs: legacy applications and other programs on enterprise networks may not be as effective and may even pose security challenges and additional expenses
• Communicating between moving entities: car-to-car, car-to-object, car-to-people communication has its unique challenges which require collaboration between many stakeholders – from cities to auto dealers, from government officials to 5G developers, from business leaders to consumers
• Infrastructure and Policy Challenges: we need the policies, support and funding so that we can invest in infrastructure upgrades which further allow for innovating on the edge

Below are best practices for innovating on the edge.

• Practice Data Gravity, which treats data at its origination site, rather than moving it to another location before working with it. This addresses the data issues around latency, storage and movement.
• When filtering for relevant data on the edge, the algorithms don’t need to be that precise, just identifying data that’s in the right ballpark.
• Invest in solutions which minimize latency, especially when lives are at stake –  for example for healthcare and automotive solutions.
• Design smaller form factors but with more functionality and more control.
• Get immediate, deep and broad visibility on security exposure and breaches.
• Create and join partnerships with carriers, vendors, providers, regulators to support the infrastructure needed to innovate on the edge.
• Look to the AI for the historical trends and integrate that into your solution,  while also looking at Machine Learning to make predictions based on past behaviors and information.
• Optimize for tiny computers on the Edge, which can do much more processing more quickly. 
• Design more sophisticated environmental sensors which would give real-time feedback, monitoring for specific issues. 
• Pay close attention to the user experience – what’s intended and what’s experienced. 

The bottom line is that we will all continue to innovate on the edge, and companies and consumers will continue to reap the benefits of it in our day-to-day lives. 
Resource: March 8, 2021: Global Mission Critical Communications Market Report 2021: AI-powered IoT Critical Communication Market in Public Safety will Surpass $20 Billion by 2028 https://www.prnewswire.com/news-releases/global-mission-critical-communications-market-report-2021-ai-powered-iot-critical-communication-market-in-public-safety-will-surpass-20-billion-by-2028-301242381.html

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