It’s been hard to miss all the hype about artificial intelligence and how it will transform everything it touches. The latest trend is toward “AI at the edge” of IoT deployments, the edge being where the data is generated from devices, typically sensors, that monitor various characteristics of the equipment they’re attached to. At the moment, nearly all this data is sent to cloud data centers, which causes two major problems: high end-to-end latency and a massive burden on the communications pathway between the edge and the cloud. In addition, as even a relatively small IoT deployment can generate huge amounts of data, it’s becoming increasingly obvious that some of this processing should be performed at the edge.
Reducing latency is far from trivial, as the laws of physics dictate the minimum time that can be achieved for a signal traversing a given distance and back. The least latency will always be delivered over the shortest distance, taking into consideration the processing, computing, and other functions performed along the way. For IoT, this is data traveling outward from the edge device to the cloud, and the return response from the cloud to the device (Figure 2).