Edge AI

What is Edge AI:
Edge AI enables abilities in devices to run data processing and data analytics locally on the device using data that they create so that they can make decisions in the form of output without the need to take the data to the cloud each time.

How Edge AI Works
Before Edge AI came about, smart devices would send all data to the Cloud. You’ve probably heard the term Big Data. Named after the massive influx of datasets that resulted in part from the IoT, Big Data has become a growing field that attempts to structure and make sense of massive datasets. The processing of this data, such as critical datasets in the medical and industrial sectors, will vastly improve things like the ability to predict and respond (almost) immediately to emergencies. Unlike traditional machines, Edge AI devices will analyze and process incoming data at the source and determine what needs to be processed by more powerful algorithms in the Cloud, versus what can be processed locally. For example, if you tell the Amazon Echo, “Alexa, let’s play a game,” or “Alexa, tell me a joke,” the games and jokes available are stored in and processed by the device’s local hardware. This will not require sending data to the Cloud. The device can execute the function (and keep the user happy) without bogging down the Cloud-network. If instead, you ask Alexa about the weather, the device will need to search an external source (in the Cloud) for that data.

Benefits of Edge AI
It solves both security concerns pertaining to storing personal user information in the Cloud and also reduces strain on Cloud networks by processing data locally. It also enables the processing of data in real-time, currently not possible with traditional, cloud-powered smart devices, but critical for technologies like autonomous vehicles and medical devices.

Current and Future Applications:
A few existing platforms include smart speakers like Amazon’s Echo and Google’s Home. In the energy and industrial space, some companies have developed systems with predictive sensors and algorithms that monitor the health of the components to notify technicians when maintenance is required.
In the future, there is talk about developing Edge AI-based systems in hospitals and assisted living facilities to monitor things like patient heart rate, glucose levels, and falls (using cameras and motion sensors). These technologies could be life-saving and, if the data is processed locally at the edge, staff would be notified in real-time when a quick response would be essential for saving lives.
Edge AI is an exciting new technology that continues to be talked about and developed. It will only be a matter of time before Edge AI-powered devices (like the IoT) becomes a way of life.