Time-Series Anomaly Detection in Off-Grid Solar-Powered Security Systems Using Deep Learning Approaches
Reliable operation of off-grid solar-powered security systems is essential for maintaining uninterrupted surveillance and monitoring in remote locations. This study proposes a fully unsupervised deep learning framework for detecting energy-related anomalies in multivariate solar-system time-series data before they affe...