There are three types of data produced in the edge devices - video, audio and other sensor data. Video-based analytics tend to be more complex as each video is a collection of images per second and the image itself will have multiple channels - Red, Green and Blue. With advances in cameras, vision-based analytics are gaining momentum across many applications - smart video doorbells, video surveillance, drones, robots, autonomous vehicles and last mile delivery. Fundamentally, there are three functions one can implement with vision-based analytics as shown in Figure 1-1: Classification, Detection and Segmentation. You can see from the same image, three different functions that can be implemented based on vision-analytics in an edgeAI system - starting from classifying the image to pixel level analysis of the entire scene.

Figure 1-1 Top three vision AI functions