This project explores the potential of the Hierarchical Temporal Memory (HTM) algorithm for this purpose, aiming to address challenges such as noise, concept drift, and unknown anomalies. We propose a specialized variant, "Grid HTM," designed to enhance video anomaly detection, making it more adaptive and reliable.