Electronic Device Directory for Suspect Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Law enforcement agencies face difficulties in identifying and locating suspects due to population density and mobility, as well as limitations in video surveillance, including limited field of view, incomplete images, and the sheer volume of video evidence.
Innovation Solution
Creating an electronic device directory that compiles registrations of devices such as cell phones and PDAs in areas associated with similar events, by comparing device registration captures across events to identify common devices, and filtering out resident devices to focus on potentially suspect individuals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If video surveillance cameras are deployed to cover specific areas, then the ability to capture images of persons in the area is improved, but the field of view is limited and only a portion of the area can be monitored at once
Solution Approach 1:
The system segments the monitoring task by dividing the area into multiple zones covered by different cameras, then uses the mobile device location data to determine which segmented camera feeds are relevant to the investigation, allowing comprehensive area coverage while focusing computational resources on relevant segments
2Quantity of substance
If multiple video cameras are deployed to increase coverage, then the ability to capture events is improved, but the sheer volume of video evidence increases making analysis difficult
Solution Approach 1:
The system performs preliminary action by obtaining and processing mobile device location information before analyzing video evidence. This allows the system to pre-identify devices of interest and their locations, so that when video analysis is performed, only relevant camera feeds and time periods need to be examined, dramatically reducing the time required to analyze large volumes of video evidence from multiple cameras
Solution Approach 2:
The mobile device location data serves as an intermediary that bridges the gap between the large number of cameras and the investigation goals. Instead of directly analyzing all video feeds, the system uses location data to filter and prioritize which camera feeds are relevant, making the video analysis process efficient despite the large number of cameras deployed
3Measurement precision
If video surveillance is used to identify persons, then the ability to capture images is improved, but images may be incomplete or persons may be intentionally obscured making identification difficult
Solution Approach 1:
The system uses mobile device identification data as an intermediary to supplement incomplete video information. When video images are obscured or incomplete, the system can cross-reference with mobile device data (device ID, location, time) to identify persons of interest, providing an alternative identification pathway that compensates for poor image quality
4Adaptability or versatility
If law enforcement agencies expand their jurisdictional coverage to catch mobile criminals, then the ability to locate suspects is improved, but communication and information sharing between agencies becomes more difficult
Solution Approach 1:
The system implements a universal database architecture where mobile device information is stored and accessible by multiple law enforcement agencies through a standardized interface. This allows different agencies with different jurisdictions to access the same device data without complex point-to-point communication arrangements, enabling universal access while maintaining system simplicity
Data Source
AI summary
A manner of creating an electronic device directory containing the identity of electronic devices that registered in an area associated with a plurality of events, which events are similar in certain respects. The directory is useful, for example, investigating criminal cases. When such an event occurs, an application server is notified and generates one or more device registration capture requests to determine which electronic devices are registered in the area and at approximately the same time at which the event occurs. The device registration capture associated with this event is compared with other device registration captures associated with other, similar events to create the electronic device directory. The electronic device directory entries are preferable filtered to select the devices most likely to be associated with the actual events in question.