Prioritizing Evidence Leads via Device Mobility Parameters
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Solution Overview
Problem
Gathering incident scene information from witnesses is challenging due to the decline in quality and difficulty in tracking down witnesses, especially in transient populations, leading to an initial influx of evidence leads that are hard to prioritize effectively.
Innovation Solution
A communication system and method that uses geographic mass messaging notifications to prioritize incident feedback responses based on device parameters such as location and mobility, assigning higher priority to transient devices likely to leave the incident area, allowing for quick follow-up before reviewing the content of their responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If mass messaging notifications are sent to all devices in the incident area, then the quantity of evidence leads increases, but the difficulty of prioritizing which witnesses to follow up with increases
Solution Approach 1:
The system changes parameters associated with each responding device (location, mobility metrics, time stamps) and uses these parameter changes to automatically prioritize evidence leads. By monitoring parameter changes such as device movement patterns and location updates, the system can dynamically rank witnesses without manual intervention.
Solution Approach 2:
The patent replaces manual investigative prioritization with an automated electronic system that uses algorithms to process device parameters and mobility data. This substitution of mechanical/manual processes with automated computational methods resolves the complexity of manually prioritizing large volumes of evidence leads.
2Manufacturing precision
If investigators manually review all incident feedback responses, then the quality of evidence collection improves, but the time required for evidence collection increases
Solution Approach 1:
The system performs preliminary automated prioritization of evidence leads based on device parameters before investigators conduct detailed reviews. By pre-ranking witnesses using automated analysis of mobility and location data, the system prepares the evidence pipeline in advance, allowing investigators to focus on high-priority leads first.
Solution Approach 2:
The system continuously monitors device parameters and updates priority rankings based on ongoing feedback from device behavior. As witnesses move or change their device status, the system receives feedback and dynamically adjusts prioritization, ensuring investigators always work on the most current high-value leads.
3Manufacturing precision
If investigators focus on transient witnesses first, then the completeness of evidence collection improves, but the difficulty of identifying transient devices increases
Solution Approach 1:
The patent replaces manual identification of transient witnesses with automated electronic monitoring of device parameters. The system automatically detects transient devices by analyzing mobility metrics, location changes, and device behavior patterns, eliminating the need for investigators to manually determine which witnesses are transient.
Solution Approach 2:
The system introduces device parameters and mobility data as intermediaries between the witnesses and the investigators. These intermediaries provide objective, measurable indicators of transience that automatically flag transient devices, making them easily identifiable without direct investigator judgment.
Data Source
AI summary
A communication system and method are provided for prioritizing the collection of evidence leads. Geographic mass messaging notifications are sent out alerting to an incident in conjunction with a request for incident information. Responding devices are prioritized based on device parameter information. The prioritization enables transient devices to be provided with a higher priority than non-transient devices. The assigned priority facilitates investigative follow-up of a plurality of evidence leads prior to the review of actual data content of each lead.