Anomaly Detection Analytics System Using Multi-Source Data Correlation
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Solution Overview
Problem
Current surveillance systems lack an efficient technique for automatically detecting anomalous events in images and determining their likelihood, which can lead to delayed or inaccurate responses to potential threats.
Innovation Solution
An analytics system that processes images from image capture systems, utilizing historical and social media data to calculate a confidence score for anomalous events, and adjusts this score based on similarity analysis with other events, enabling automatic action such as alert transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If surveillance systems use manual monitoring of images, then detection accuracy can be maintained, but processing time and resource consumption increase significantly
Solution Approach 1:
The system enables automated event detection and anomaly scoring through self-service mechanisms, where the analytics system independently processes images, correlates multi-source data, generates anomaly scores, and triggers alerts without human intervention, thereby maintaining detection accuracy while dramatically reducing processing time
Solution Approach 2:
The patent replaces manual mechanical monitoring with automated electronic processing systems that use image analysis algorithms, data correlation mechanisms, and automated scoring systems to detect events and determine anomalies, eliminating the time-consuming manual review process while preserving or enhancing detection capabilities
2Reliability
If surveillance systems process all images manually, then detection thoroughness is maintained, but resource consumption increases
Solution Approach 1:
The system applies partial action by selectively processing only those images that contain detected events rather than manually reviewing all images, using automated anomaly scoring to identify which cases require further investigation, thereby maintaining detection thoroughness for critical events while reducing overall resource consumption
Solution Approach 2:
The automated system performs self-service by independently evaluating images, correlating data from multiple sources, generating anomaly scores, and determining which cases warrant further attention, eliminating the need for exhaustive manual review of all surveillance footage while maintaining reliable detection of significant events
3Productivity
If automated event detection is implemented, then processing efficiency improves, but detection accuracy may deteriorate
Solution Approach 1:
The system introduces an intermediary automated analytics layer that bridges raw image data and final detection results, using multi-source data correlation and anomaly scoring mechanisms to enhance the reliability of automated detection, thereby maintaining processing efficiency while improving or preserving detection accuracy through intermediate analysis steps
Solution Approach 2:
The system implements feedback mechanisms where anomaly scores and detection results are continuously refined based on correlated data from multiple sources, allowing the automated system to learn and improve its detection accuracy over time while maintaining high processing efficiency through automated decision-making processes
Data Source
AI summary
A device may receive, from one or more other devices, one or more images that depict one or more events occurring at a location. The device may detect an event of the one or more events depicted in the one or more images. The device may determine a first score that indicates a first likelihood that the event is an anomalous event. The device may determine a second score that indicates a similarity between the event and another event. The second score may be based on second data received from the one or more other devices. The device may determine a third score based on the first score and the second score. The third score may indicate a second likelihood that the event is the anomalous event. The device may perform an action based on the third score.