👉 Surveillance math, often rooted in information theory and statistics, involves the mathematical analysis of data collected through surveillance systems to understand patterns, predict behaviors, and ensure security. It uses concepts like entropy to measure uncertainty in data, allowing analysts to quantify the amount of information in surveillance footage or signals. Techniques such as frequency analysis and correlation help identify anomalies or patterns that might indicate suspicious activity. By applying these mathematical tools, surveillance systems can optimize their performance, enhance security measures, and make more informed decisions based on the data they collect.
