It’s middle of the night and I wake up feeling thirsty. Hearing a faint rhythm of a song I know from years ago, I walk towards the window holding a glass of water. I try to listen and voilà, it is indeed the familiar music of youth.
It makes me smile to think how the meaning of this phrase ‘living on the edge’ has travelled the distance of a few light years. I now work in the information technology industry, where edge is the guiding light into everything intelligent, responsive, real time and predictive.
The edge of today, as in edge computing, is not pushing my blood pressure up or making me flush with adrenalin. It is rather helping industries improve efficiency, safety and productivity.
I read “Business at the Speed of Light” by Bill Gates long ago. The practical implications of that title are being seen now. While IoT is already proving to be a critical enabler on the factory floor, organizations are now looking to enhance the responsiveness of their manufacturing systems further. Manufacturers envision a future where factory equipment can make autonomous decisions based on what’s happening in real time. A future where they can more easily integrate all steps of the manufacturing process including design, manufacturing, supply chain and operations which will facilitate greater flexibility and reactivity when participating in competitive markets. Enabling this vision requires a combination of related technologies such as IoT, artificial intelligence, machine learning, and most importantly, edge computing.
A simpler definition of edge is the end point where the action is happening. Edge computing is processing the data as close to the source as possible instead of the traditional process of collecting data using sensors from a manufacturing process and sending that data to a PLC (Programmable Logic Controller).
Machines generate humongous amounts of data and that is fed into the cloud through bandwidth in order to analyze it, sending instructions back to actuators to adjust the process. There is another way to make use of IOT devices. Collect, analyze at the edge of the network and execute on real-time data without the bandwidth costs and the added expense of time that comes with sending that data offsite for analysis. It is the distributed framework where data is processed as close to the originating data source as possible. This has many advantages over cloud computing, most notably the reduction of latency and infrastructure costs. Overall, being at the scene of the action, edge improves data reliability while saving the costs of duplication.
IoT involves collecting data from various sensors and devices and applying algorithms to the data to glean insights that deliver business benefits. Industries ranging from manufacturing, utility distribution, traffic management, retail, medical and even education are making use of the technology to improve customer satisfaction, reduce costs, improve security and operations and enrich the end user experience.
Two drivers of edge technology today are high speed operations and processes that generate large amounts of data. High speed operations can create latency problems. Computing closer to the edge or directly on a machine reduces latency. Additionally, the device could operate independently, which may improve security by not having to access a large network.
The best thing I have read about data processing was from Nick Fragale, co-founder of Rover Robotics, who said “run on the edge, train in the clouds.” I hear the same old familiar tune and wonder how the band performing the song in my head would react to the new meaning of what they once served up as the epitome of rebellion.