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Edge Computing: Enabling Real-Time Insights and Actions
“If the edge device if it has enough memory, you can process and archive data there, and it can be uploaded to the cloud later when it’s convenient,” Ressler said. “You also could use edge computing to make decisions on the device in real time, and also be sending some data to the cloud to be analyzed, but not relying on the cloud for any real-time decisions.” That strategy can help organizations reduce their cloud bill, and also can be effective in use cases where intermittent connectivity is an issue, such as at construction sites or mining sites.
Brown added, “It’s not a ‘versus’ situation.” Cloud computing and edge computing are complementary. “The reality is the amount of processing that people want to do is going up and up and up. You need that continuum of processing power.”
There are many factors involved in the Internet of Things. Ten years ago sensors were not small enough or did not have the computing power of sensors today. The fact that a sensor today can now actually crunch the numbers for the data it is collecting and provide real actionable data or situational awareness to the “Edge” and on to the “Cloud” means that data can be analyzed at multiple levels simultaneously. Manufacturers will need to use the data collected at the Cloud and Edge levels to identify updates that can be made to sensor algorithms to make those algorithms more efficient. Many algorithm updates could even be made automatically with the use of AI modules built into cloud and edge processes.