Audio-Video Analytics for Security Monitoring

The patent combines video data and audio data into an integrated monitoring system that processes both modalities simultaneously. The audio analytics engine and video analytics engine work together to provide complementary information, where audio data captures contextual cues (shouting, breaking glass, alarms) that video alone might miss, while video provides visual confirmation. This merging resolves the contradiction by preventing information loss from audio while avoiding the inefficiency of relying solely on video storage.

The patent introduces an audio analytics engine as an intermediary component that processes audio data independently before integrating it with video analysis results. This intermediary layer filters and interprets audio signals (identifying gunshots, screams, glass breaking) and uses them to supplement or override video-based determinations, thereby recovering contextual information that would otherwise be lost without requiring continuous video storage for all scenarios.

The system performs preliminary audio analysis to identify potential security events (gunshots, screams, glass breaking, alarms) before triggering video recording or full monitoring. This preliminary action filters out normal ambient sounds using machine learning models trained on security-relevant audio patterns, activating video storage only when audio indicators suggest a genuine threat, thereby saving storage resources while maintaining detection accuracy for critical events.

The patent implements feedback loops where audio analysis results continuously inform video monitoring decisions and vice versa. When audio detects a potential threat, the system activates video recording and intensifies monitoring; when audio confirms normal conditions, video storage is reduced or paused. This feedback mechanism ensures that storage resources are allocated dynamically based on actual security needs, preserving detection accuracy while optimizing resource usage.

The system employs periodic audio sampling and analysis instead of continuous video monitoring during low-risk periods. Audio sensors continuously monitor for security-relevant sounds (gunshots, screams, glass breaking) and only trigger video recording when anomalies are detected. This periodic action maintains reliable monitoring coverage for critical events while dramatically reducing storage resource consumption during normal, threat-free periods.

The patent applies partial monitoring action by using audio-only monitoring as the baseline and activating full video monitoring only when audio indicators suggest a potential threat. This partial action approach provides sufficient monitoring coverage for security-critical events while avoiding the resource waste of continuous video storage, allocating storage resources proportionally to the actual security risk level.