Asset Tracking Coverage Mapping for Cellular Dead Zones
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Solution Overview
Problem
Asset tracking devices often encounter dead zones or low-quality network coverage, leading to unresponsive devices and potential misinterpretation of device failure, especially when handling assets with special handling requirements and sensor data needs.
Innovation Solution
A system that generates a detected coverage plan from asset tracking device location reports, creating geographical maps of network coverage and dead zones, and provides notifications to users about potential loss of connectivity, while also optimizing mobile network plans based on device location history using machine learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If asset tracking devices rely on cellular network coverage for continuous reporting, then location data can be transmitted regularly, but devices become unresponsive in dead zones or low-quality coverage areas
Solution Approach 1:
The system performs preliminary actions by generating coverage maps in advance using historical location data before devices enter dead zones. These pre-generated maps allow the system to predict connectivity loss and notify users before devices become unresponsive, enabling proactive rather than reactive responses to coverage issues.
Solution Approach 2:
The system implements feedback by continuously collecting location data from multiple devices, analyzing network coverage patterns, and using this information to generate updated coverage maps. This feedback loop enables the system to learn from actual device performance and improve coverage predictions over time.
2Measurement precision
If coverage maps are generated using historical location data from multiple devices, then accurate network coverage patterns can be identified, but data processing and map generation complexity increases
Solution Approach 1:
The system applies universality by using a single centralized server to perform multiple functions: collecting location data from numerous devices, processing and analyzing coverage patterns, generating coverage maps, and notifying users. This multi-functional approach consolidates complexity into one system rather than requiring each device to independently process and analyze data.
Solution Approach 2:
The system merges data from multiple independent sources (location reports from many different devices) into a unified coverage map. By combining disparate data points into a single comprehensive view, the system achieves high accuracy without requiring complex processing at each individual device level.
3Reliability
If users are notified about upcoming connectivity loss, then preventive actions can be taken, but additional notification infrastructure and processing are required
Solution Approach 1:
The system uses an intermediary approach by introducing a centralized server that acts as a mediator between the coverage map data and users. The server analyzes coverage patterns, determines when devices are approaching dead zones, and handles notification delivery. This intermediary layer simplifies the architecture compared to having each device independently monitor and notify about coverage issues.
Data Source
AI summary
Methods and systems for building a coverage map for a mobile network operator based on a plurality of location reports received from a plurality of deployed asset tracking devices, the reports including geolocation data and mobile network identifiers. On request from a user device the coverage map is used to generate an overlay atop a geographical map showing the boundaries of coverage for that mobile network operator.