Central Server Crime Investigation System
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Solution Overview
Problem
Current methods for investigating organized retail crime (ORC) are inefficient due to the large volume of surveillance data across multiple locations, making it difficult to identify repeat offenders and correlate patterns, which hinders quick action and asset recovery.
Innovation Solution
A computer-enabled system and method that utilizes a central server to aggregate and analyze surveillance data from multiple locations, performing historic and active searches, and issuing alerts to predict future criminal activity, using facial recognition and social media searches to update suspect locations and crime patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If investigators manually search surveillance video from multiple stores, then they can identify suspects and patterns, but the investigation time becomes prohibitively long
Solution Approach 1:
The system performs preliminary actions by automatically analyzing surveillance footage and creating suspect profiles before investigators begin their work. The automated system pre-processes video data, identifies potential suspects, and organizes information so that investigators can immediately act on pre-prepared intelligence rather than starting from scratch.
Solution Approach 2:
The patent replaces the manual mechanical process of watching and analyzing surveillance video with an automated computer-based system. The automated analysis system uses algorithms to process video data, identify suspects, and correlate information across multiple stores, substituting human investigators' manual review with automated mechanical processing that is both faster and more consistent.
2Loss of information
If investigators review all surveillance data from multiple locations, then they can identify repeat offenders, but the complexity of data management increases
Solution Approach 1:
The system merges surveillance data from multiple store locations into a centralized database, combining video footage, suspect information, and crime patterns into a unified system. This consolidation allows investigators to access all relevant information from multiple locations through a single interface, reducing the complexity of managing separate data systems while maintaining complete evidence correlation.
Solution Approach 2:
The patent introduces an automated analysis system as an intermediary between the raw surveillance data and the investigators. This intermediary automatically processes, filters, and organizes data from multiple locations, presenting only the most relevant information to investigators. The intermediary handles the complexity of data aggregation and correlation, freeing investigators from direct engagement with the complex data management tasks.
3Speed
If the system monitors all store locations in real-time, then it can detect crimes quickly, but the computational resources required increase
Solution Approach 1:
The system applies local quality by focusing computational resources on specific areas or time periods where criminal activity is suspected or has been detected. Rather than uniformly monitoring all stores with equal intensity, the system dynamically adjusts its monitoring focus to high-risk locations and times, maintaining fast detection capability where needed while conserving computational resources in lower-priority areas.
Solution Approach 2:
The patent implements periodic action by analyzing surveillance data in scheduled intervals rather than continuously processing every frame from all cameras simultaneously. The system uses periodic analysis cycles to review footage, allowing it to maintain effective monitoring across multiple locations while managing computational load through time-based resource allocation rather than requiring peak resources at all times.
Data Source
AI summary
A system and method for investigating crimes occurring at locations that are communicatively connected by a central server is disclosed. The investigation is highly automated and obtains evidence using computer aided searches of historic surveillance data gathered at locations within a computer search area. The investigation also utilizes active searches of real-time surveillance data gathered at the locations in response to a be-on-the-look-out (BOLO) alert sent to the locations from the central server. Based on evidence obtained from these searches, the search area may be updated and the searches may be repeated to follow a moving crime pattern/route. In addition, the information provided from the searches may facilitate the prediction of a location that is likely to experience a crime in the future. Accordingly, the central server may transmit a high alert to the predicted location.