A. B

TinyML-based Autoencoder for Real-Time Anomaly Detection in Resource-Constrained IoT Sensor Streams

Anomaly detection of sensors within small hardware platforms such as ESP32 is complicated by its lack of memory space and computational capabilities. This paper presents a lightweight anomaly detection model that uses autoencoders, developed and optimized using the TensorFlow Lite Micro framework. The model was trained...