Route Optimization Using Network Connectivity and Safety Alerts
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Solution Overview
Problem
Current mobile navigation systems do not effectively incorporate network condition data to optimize routes for reliable connectivity, and they lack proactive safety alerts based on real-time crime and event data, which can impact user experience and safety.
Innovation Solution
A system that integrates mobile computing devices, a crowdsourcing server, and a GIS server to determine routes based on network condition data and provides proactive safety alerts by using crime and event data, optimizing routes for improved connectivity and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If navigation systems use traditional shortest distance or travel time routing, then route efficiency is improved, but network connectivity reliability deteriorates
Solution Approach 1:
The patent changes the routing parameters by incorporating network condition data (signal strength, connectivity quality) as additional factors alongside traditional distance and time metrics. The system dynamically adjusts route selection based on real-time network parameters, transforming the routing problem from a single-objective optimization to a multi-parameter optimization that balances travel efficiency with connectivity reliability.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring network conditions along proposed routes and using this information to adjust routing decisions. Network condition data collected from multiple sources is fed back into the routing algorithm to dynamically modify path selection, ensuring that routes maintain reliable connectivity while still achieving efficient travel.
2Adaptability or versatility
If mobile devices provide multiple applications for entertainment and productivity, then user functionality is improved, but network data connection reliability deteriorates
Solution Approach 1:
The system performs preliminary actions by proactively identifying and selecting routes with optimal network conditions before the user begins their journey. By pre-planning paths based on anticipated network quality, the system ensures that multiple applications can function reliably throughout the trip without encountering connectivity interruptions.
Solution Approach 2:
The patent modifies the approach to network connectivity by changing from passive connection attempts to active route selection based on network parameters. The system evaluates network conditions as a primary factor in route determination, ensuring that the selected path maintains parameters suitable for supporting multiple simultaneous applications.
3Ease of operation
If GIS data is made available for manual searching and browsing, then user control is improved, but user safety and awareness deteriorates
Solution Approach 1:
The system implements self-service by automatically providing safety information and alerts without requiring manual user action. While users retain control over their navigation, the system independently monitors and communicates safety conditions, crime data, and environmental factors, freeing users from the need to manually search for this critical information.
Solution Approach 2:
The patent introduces an intermediary layer that processes and filters safety and crime data, then presents relevant information to users in context. This intermediary system bridges between raw GIS data and user needs, automatically delivering safety alerts and information without requiring users to directly interact with complex data sources.
Data Source
AI summary
Examples disclosed herein include a mobile computing device to determine network condition information associated with a route segment. The route segment may be one of a number of route segments defining at least one route from a starting location to a destination. The mobile computing device may determine a route from the starting location to the destination based on the network condition information. The mobile computing device may upload the network condition information to a crowdsourcing server. A mobile computing device may predict a future location of the device based on device context, determine a safety level for the predicted location, and notify the user if the safety level is below a threshold safety level. The device context may include location, time of day, and other data. The safety level may be determined based on predefined crime data.