Description: Edge AI analytics refers to the use of artificial intelligence techniques to analyze data at the edge of the network, that is, close to where the data is generated, rather than sending it to a central server for processing. This methodology allows for real-time insights and facilitates quick and efficient decision-making. By performing analysis at the edge, latency is reduced, bandwidth usage is optimized, and data privacy is improved, as the transfer of sensitive information across the network is minimized. Key features of edge analytics include the ability to process large volumes of data locally, the integration of machine learning algorithms, and adaptability to different environments and devices. This technology is particularly relevant in an increasingly connected world, where the Internet of Things (IoT) and smart devices continuously generate data. Edge AI analytics is becoming an essential tool for various industries, as speed and accuracy in decision-making are crucial for operational success.
