Artificial intelligence seems to be far away from us, but it has already come to people's daily lives. Many people come into contact with artificial intelligence when they use their smartphone's voice-to-text conversion assistant or fingerprint recognition applications every day. In IoT applications, artificial intelligence can help identify patterns of IoT edge devices and detect changes in related parameters. These IoT edge devices are typically equipped with sensors that sense changes in environmental factors such as temperature and pressure.
Typically, a simple embedded edge device collects data from sensors in the application environment and transmits the data to the cloud, where the data is analyzed and reasoned by an artificial intelligence system in the cloud infrastructure. However, as the demand for real-time decision making continues to grow during the implementation of the Internet of Things, the need for connectivity and data processing is increasing, and it is not always possible to transmit all of the data to the cloud for artificial intelligence processing. This article aims to explore how deploying artificial intelligence at the edge can improve the efficiency and efficiency of the IoT and reduce costs.