Dashboard Computing Device for Missing Digital Evidence Identification
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Solution Overview
Problem
Reviewing digital evidence of public-safety incidents is time-consuming and prone to errors, leading to potential misclassification of offenses due to missing or incomplete digital evidence, which can result in lesser offenses being prosecuted instead of greater ones.
Innovation Solution
A dashboard computing device system that receives and compares digital evidentiary items from various jurisdictional agencies, identifies missing evidence, and electronically requests it from the most likely agency to have access, using a digital offenses-to-evidentiary-items mapping to ensure accurate classification and prosecution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual review of digital evidence is performed, then flexibility in evidence evaluation is maintained, but time consumption and error rate increase
Solution Approach 1:
The patent replaces manual mechanical review processes with an automated computing system that uses algorithms to collect, manage, and analyze digital evidentiary items. The system automatically determines offense types and generates recommendations, substituting human manual evaluation with computational processing to reduce time while maintaining or improving accuracy.
Solution Approach 2:
The system enables self-service by automatically collecting evidentiary items from multiple sources, comparing them against required items for different offenses, and generating its own recommendations without requiring continuous manual intervention. The computing device independently manages the evidence review process, reducing reliance on manual labor.
2Loss of information
If comprehensive digital evidence collection is performed across multiple jurisdictions, then completeness of evidence improves, but system complexity increases
Solution Approach 1:
The computing device is designed with multi-functionality to handle diverse evidentiary items from multiple jurisdictional agencies. It can collect, store, compare, and analyze different types of digital evidence (videos, images, data) from various sources through a unified interface, reducing the perceived complexity for users while achieving comprehensive evidence collection.
Solution Approach 2:
The patent introduces a central computing device as an intermediary between multiple jurisdictional agencies. This intermediary consolidates evidence from various agencies, standardizes the data format, and presents a unified view to prosecutors, thereby reducing the coordination complexity that would otherwise exist between multiple independent agencies.
3Productivity
If automated systems are used to review digital evidence, then processing speed increases, but risk of algorithmic errors increases
Solution Approach 1:
The system incorporates feedback mechanisms where the computing device generates recommendations based on its analysis, but these recommendations can be reviewed and adjusted by prosecutors. The system learns from and adapts to feedback, improving its accuracy over time while maintaining high processing speed. The feedback loop allows correction of algorithmic errors while preserving automated efficiency.
4Loss of information
If manual identification of missing evidence is performed, then judgment-based prioritization is possible, but time and human resources are consumed
Solution Approach 1:
The patent replaces manual identification of missing evidence with an automated comparison process. The computing device systematically compares collected evidentiary items against the required items for determined offense types, automatically identifying gaps without requiring human time or resources for this specific task.
Data Source
AI summary
A device, system and method for electronically requesting and storing missing digital evidentiary items is provided. A dashboard computing device: receives, from distinct jurisdictional agency computing devices, indications of jurisdictional digital evidentiary items associated with an incident; determines, based on an incident type of the incident, one or more offenses associated with the incident type; determines required digital evidentiary items to prosecute the offenses via a digital offenses-to-evidentiary-items mapping; identifies a missing digital evidentiary item for prosecuting the offenses by: comparing the indications of the jurisdictional digital evidentiary items with the required digital evidentiary items; identifies a jurisdictional agency, associated with one or more of the distinct jurisdictional agency computing devices, that is most likely to have access to the missing digital evidentiary item; and renders, at a display screen, an actuatable option for electronically requesting the missing digital evidentiary item from the jurisdictional agency.