AI Sensor Applications in Edge Computing

Sensors play a key role as transducers, converting physical quantities into digital data for edge computing. This article discusses the application of (AI) sensors in edge computing for real-time decision-making and power consumption re-duction. Conventional sensors tend to overload edge devices with unwanted data such as interference, false alarms, and coupling data, thereby hindering real-time responses. In contrast, AI sensors utilize the data screening technique, which offers a solution by selectively sending only relevant data to edge computing devices. By integrating multiple sensing elements and adaptable algorithms, AI sensors enable real-time decision-making with precise responses and reduce power consumption in a wide range of applications. This article describes the architecture of AI sensors and highlights their advantages over conventional sensors, specifically in current sensor applications. Through simulations, the effectiveness of AI sensors in combining multiple sensing elements and embedded algorithms was demonstrated. The integration of AI sensors and edge computing elevates the capabilities of devices for mission-critical applications.