Working at the Edge: Bringing the power of analysis closer to man and machine
This article was first published in RT Insights
As the 5G market matures, we expect astronomical growth in the volume of data residing at the Edge – offering more informed decisions leveraging real-time, actionable information.
Fueled by the large volume of data being moved, processed, and stored in the Cloud, as well as the new realities of a hybrid and distributed workforce and the insatiable demand for actionable insights, the number of organizations leveraging Edge computing will continue to increase in the coming years.
Edge computing executes computation at or near the physical location of either the user or their data source – to optimize the outcomes being delivered by one’s applications and/or devices. Data generated by mobile devices, sensors, and connected machinery can now reside much closer to the point of decision making and fulfillment. Edge computing introduces a computing model that is truly distributed and consequently more secure as well as efficient. Critical computing that needs to be done quickly (prioritized by use case) can be executed at the Edge for speed and then reported back to the Cloud (the back-end system of record).
Edge computing is already in use all around us – from the wearable on your wrist to the systems intelligently parsing traffic flows at your nearest intersection. Other examples of how ubiquitous Edge computing has become include smart utility grid analysis, safety monitoring of oil rigs, streaming video bandwidth optimization, and drone-enabled crop management solutions.
The Tesla autopilot is an Edge computing use case and is now helping drivers around the world in more than 2 million vehicles. The car computes at the Edge for rapid spatial decision-making based on local spatial data collection. It then reports what it “saw” and what it “did” to the Tesla neural network, which can then update all the other Edge computing devices (cars in the fleet) as to what the correct decision was for that specific situation. Edge computing is an extension of the Cloud where certain time-sensitive tasks are intelligently distributed for improved efficacy at the Edge of the network.
Retailers are combining Edge computing with complementary emerging technology solutions like computer vision, augmented reality (AR), virtual reality (VR) , and even light detection and ranging (lidar) technology. Offline shopping is being reinvented using customer-centric technology that can identify, map, and anticipate consumer preferences within fully automated, cashier-less stores. Cashier-less checkout experiences like Amazon Go, Starbucks, Circle K, and Kroger may very well be the future of the “experiential” retail environment as they move towards a seamless self-service shopping experience in the post-pandemic world.
Today, consumers have an expectation of speed, convenience, and enhanced safety protocols. By deploying Edge computing, retailers can drastically reduce delays and costs associated with network congestion while offering more security around consumers’ personal data. Data privacy can be enhanced as sensitive image and video data, which frequently includes personally identifiable information, can now be processed locally without being sent via a network to be stored in the Cloud. Removing the need to transport the data helps minimize the risk of a security breach that could expose this information.
Recent advances in telecommunications technology, specifically 5G, has made Edge computing even more powerful and a compelling consideration when designing innovative new solutions across industry verticals. As the 5G market matures, we expect astronomical growth in the volume of data residing at the Edge – offering more informed decisions leveraging real-time, actionable information. This powerful new technology offers great value to organizations across multiple industry verticals, from manufacturing to energy and utilities. Typical applications include predictive asset maintenance, asset utilization and optimization, anomaly detection and quality control, and many more. The combination of the incredible speed of 5G connectivity and the robust computing capabilities of Edge computing is a bona fide game-changer. By running applications and processing data with Edge computing, organizations can increase the speed by which they obtain information and gain actionable insights in near real time.
For those that have not yet explored how Edge and associated/adjacent technology can help improve efficacy, streamline cost, reduce, and control risk and tap into actionable intelligence to identify opportunities, it is never too late to embrace the future. Do your research. Work to get an understanding of Edge computing and where/how this technology can align with your business needs. Develop a relevant, clearly defined, and well-understood business use case so it is clear as to what challenge(s) you hope to address or the opportunities you wish to expose. It is critical to address these considerations at the onset of any data initiative; otherwise, you will not arrive where anticipated, and your ROI expectations may be dashed.
Scott Schlesinger is the US Data and Analytics Lead at PA Consulting