This episode investigates how context can transform detection systems from reactive alarms into intelligent decision aids. Building on the concepts of enhanced detection and contextual filtering, we explore how incorporating environmental, user, and situational cues improves accuracy, reduces false positives, and accelerates actionable insights

Key elements of context-aware detection include data fusion, feature selection, and efficient data management. We cover approaches from rule-based systems to machine learning methods that maintain privacy and clarity. Listeners will learn to design and implement adaptable detection systems. 

By the end, participants will have a framework for balancing sensitivity and accuracy, resulting in more reliable, understandable detection results with the new Ganz AI Box Pro (coming soon).