Digital Interaction Filtering for Multi-Source Forensic Visualization
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Solution Overview
Problem
Existing forensic criminal investigation techniques face challenges in effectively integrating and visualizing diverse digital interaction data from multiple sources to track and analyze interactions between individuals.
Innovation Solution
A cloud computing system is employed to create a digital interaction database that integrates and links data from various providers, enabling the creation of a graphical representation of interactions between individuals, including phone calls, messages, and social media activities, with features such as chronological listings, interaction content, and location data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If digital interaction data from multiple providers with different data structures is integrated, then the comprehensiveness of interaction tracking is improved, but the system complexity increases
Solution Approach 1:
The patent employs data normalization layers and standardized schemas as intermediaries between diverse provider data structures and the analysis engine. These intermediaries translate and harmonize different data formats (call logs, message records, social media interactions) into a unified structure, enabling comprehensive multi-source integration without proportionally increasing system complexity.
Solution Approach 2:
The system architecture is segmented into modular components: data ingestion modules for each provider type, normalization layers, relationship analysis engines, and visualization components. This segmentation allows each module to handle specific data types independently, reducing overall system complexity while maintaining comprehensive tracking capabilities across multiple data sources.
2Ease of operation
If visual representation of digital interactions is created, then the ease of analysis is improved, but the data processing requirements increase
Solution Approach 1:
The system extracts only the essential interaction attributes needed for visualization (timestamps, interaction types, relationship strength metrics) from the complete raw datasets. By selectively extracting relevant data elements rather than processing entire datasets, the system generates comprehensive visual representations while reducing computational processing requirements.
Solution Approach 2:
The visualization system implements progressive rendering that displays key relationship patterns first, then allows users to drill down into detailed interaction data as needed. This partial action approach provides immediate analytical value through high-level visual summaries without requiring complete processing and display of all raw interaction data simultaneously.
Data Source
AI summary
Some embodiments include a cloud computing system and database management for forensic criminal investigations. The cloud computing system may produce a visual representation of various digital interactions between various individuals. These digital interactions, for example, may include phone calls, text messages, emails, social media messages or posts, etc. between a first individual and a second individual. The visual representation, for example, may be provided on a webpage. The visual representation, for example, may graphically represent a relationship between the first individual and the second individual.