Gigi Joseph

An Adaptive Deep Learning Framework for Energy-Efficient Anomaly Detection in IoT Sensor Networks

An adaptive deep learning framework for anomaly detection in IoT sensor data to identify faults, intrusions, and abnormal patterns in real time is proposed, using an Autoencoder-based deep neural network that dynamically learns normal behavioral patterns and adapts to evolving data distributions.