Distributed Mobile Route Optimization for Privacy-Preserving Social Distancing
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Solution Overview
Problem
Existing systems lack effective methods to guide users to avoid close proximity while traveling, particularly in the context of preventing the spread of contagious diseases, while maintaining user privacy and avoiding centralized data collection.
Innovation Solution
A distributed processing system that includes client devices equipped with location monitoring, route selection, crossing detection, and optimization processes to select routes minimizing user crossings, using short-range radio transceivers to detect proximity without personal data exchange, and prompting users to adhere to selected routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a centralized data collection system is used to monitor user locations and routes, then route optimization for minimizing crossings can be achieved, but user privacy is compromised
Solution Approach 1:
The system divides the centralized monitoring function into distributed local processing units. Each mobile device independently performs crossing detection and route optimization calculations using its own sensor data and local algorithms, eliminating the need to centralize personal location information while maintaining collective route optimization capability
Solution Approach 2:
The patent introduces anonymous aggregated crossing data as an intermediary. Instead of sharing personal location data, devices communicate only anonymized crossing event information that allows route optimization without revealing individual user identities or specific location trajectories
2Reliability
If users are prompted to adhere to selected routes to minimize crossings, then social distancing compliance is enhanced, but user convenience and flexibility are reduced
Solution Approach 1:
The route selection system dynamically adapts to user needs and environmental conditions. The optimization algorithm continuously evaluates alternative routes and adjusts recommendations based on real-time crossing patterns, allowing the system to balance compliance enforcement with user convenience by offering flexible route alternatives rather than rigid constraints
Solution Approach 2:
The system implements feedback loops where users can provide input about their preferences and constraints, and the route optimization algorithm adjusts its recommendations accordingly. This feedback mechanism allows users to maintain flexibility while still benefiting from crossing minimization, as the system learns and adapts to individual needs over time
Data Source
AI summary
Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: counting of crossings of a mobile client with one or more neighboring mobile client during performance of a trip.