Opportunities and Challenges for Innovating on the Edge

FountainBlue’s March 13 VIP roundtable was on the topic of ‘Opportunities and Challenges for Innovating on the Edge’, with leaders from Maxim for leading the virtual discussion. Thank you also to our executives in attendance for their input and advice. Below are notes from the conversation.  

We were fortunate to have a diverse range of executives in attendance who worked in and around the edge computing field. As we grow solutions around edge computing, they agreed that it’s important to manage the following:

• Seamless connection on an ongoing basis
• Low latency/rapid response, especially when the stakes are high
• Immersive experience so people can manage and use the solutions effectively
• Connectivity wherever you go
• Privacy and security of users and their data

In order to do that, we need to do the following:

• Capture, manage and process the volumes of data generated by the growing number of sensors, devices, wearables
• Increase speed of access to the data, without a gap
• Gather, integrate, process and filter data between all sensors/devices/wearables on the edge in the cloud 
• Send back filtered/processed data back to the edge for response and action

Challenges and opportunities abound. Below are some thoughts around the data.

• Optimize the gathering/filtering/processing of data and returning only the ‘relevant’ data back to the edge/device/user
• Validate the accuracy of the data generated.
• Remember that where there is data, AI and ML can improve that data, making it more relevant and useful. 

Other challenges and opportunities are highlighted below.

• Make algorithms effective enough to be useful, small enough to not consume too much power, not take too much time to process.
• Design the architecture to better manage the power for devices/sensors/wearables on the edge.
• Make the hardware small and compact, but also simple to integrate with the firmware and software.
• The processing of images and videos will also provide many opportunities.

Below is advice on how to better innovate on the edge.

• Provide options for selecting variables and rules which impact what data.
• Validate the integrity of the data received from sources on the edge.
• Make predictions about what’s going to happen based on patterns of what’s happened in the past.
• Work with regulators so that they understand how technology works and can update their policies so that people are protected, but they can also get access to life-saving and life-improving solutions in such regulated industries as automotive and healthcare.
• Proactively manage and maintain systems, computers and machines so that they can send data about system health and issues, including issues which might be related to their own functioning.
• If you’re running multiple engineering/product teams, help them collaborate on common solutions, bringing the best brains and solutions together rather than working in silos
• Provide personalized solutions for client companies which would have immediate benefits as well as scalable impact.
• The mass adoption of 5G wireless has reached health and infrastructure obstacles, so don’t count on its adoption as part of your sales and marketing strategy for your edge computing solution.
• Create edge computing solutions which meet the ‘hard constraints’ of being on the edge: the need for POWER, the SIZE of the device, and the COST to manufacture, distribute and maintain these devices/sensors/wearables. 

We end with the staggering thought that we will soon have 42 billion connected devices. The solutions that we are providing and planning today are real use cases. But think also about what’s transformational for the future – not just what devices are sensing, but also empowering a tool/process/human/algorithm to take proactive action, based on data generated, models created. We are not quite there, and is much thinking, collaboration, and working to do before we get there, and many safeguards to put in place to make sure that’s done right.

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