Asset Bucket Correlation for Geolocated Multimedia Evidence
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Solution Overview
Problem
Law enforcement agencies face challenges in managing and correlating audio and video data captured by various devices, necessitating improved methods for organizing and analyzing multimedia assets to enhance evidence preservation and investigation efficiency.
Innovation Solution
An asset bucket is implemented as a persistent workspace on user devices, allowing for the selection, processing, and correlation of assets based on geolocation and temporal proximity, enabling efficient generation of reports and case files.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple devices from different places capture audio and video contents, then evidence preservation and investigation capabilities are improved, but management complexity and data organization difficulty increase
Solution Approach 1:
The system segments multimedia data into discrete assets with unique identifiers, organizing them by source device, location, and time. Each asset can be independently managed and correlated, reducing the complexity of handling large volumes of data from multiple devices.
Solution Approach 2:
The system introduces an intermediary data structure that correlates assets across different devices and locations. This intermediary layer abstracts the complexity of managing multiple data sources, providing a unified view while preserving the original data integrity from each device.
2Productivity
If audio and video contents are stored and managed in a network environment, then investigation efficiency is improved, but data organization and retrieval difficulty increase
Solution Approach 1:
The system performs preliminary organization of data by pre-tagging and categorizing assets based on their metadata (location, time, source device). This preliminary action enables rapid retrieval and reduces the manual organization effort during investigations.
Solution Approach 2:
The system adds dimensional organization by correlating assets across multiple dimensions (geolocation, temporal proximity, source device). This multi-dimensional indexing enables efficient retrieval operations while maintaining intuitive data organization structures.
3Measurement precision
If assets are correlated based on geolocation and temporal proximity, then analysis accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system pre-computes and stores spatial and temporal relationships between assets during data ingestion. This preliminary action enables rapid correlation queries during analysis without requiring computationally intensive real-time processing.
Solution Approach 2:
The system replaces complex real-time computational correlation with pre-established data structures and indexes. This substitution reduces processing time while maintaining accurate correlation based on geolocation and temporal proximity.
Data Source
AI summary
This disclosure describes techniques for implementing an asset bucket on user devices for organizing assets in a database. Assets may include, without limitation, stored multimedia data from various sources, grouped multimedia data, events, conditions, parameters, environmental data, and other data or telemetry data that are stored in a network operating center (NOC) server database or a third-party database. The asset bucket may include a persistent working space that can be rendered as a pane on a device's user interface for organizing assets that can be selected from a rendered window or windows on the device's user interface and/or directly inputted on the persistent working space. By configuring the asset bucket to facilitate performance of actions on the selected assets, the asset bucket may improve generation of reports on these selected assets.