Mobile Data Scheduling via Predicted Signal Strength
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Solution Overview
Problem
Traveling users often face issues with continuous cellular coverage and strength, leading to dropped calls and disconnected data connections due to bandwidth saturation in high-density areas, which existing technologies cannot effectively address by simply adding more cell towers.
Innovation Solution
A method and system that predict cellular signal strength along a user's intended travel path and schedule telephone calls and data transfers based on anticipated coverage and estimated call duration, optimizing call scheduling to improve connectivity and reduce bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If more cell towers are added to high-density areas, then cellular coverage should improve, but bandwidth saturation prevents effective connection due to limited capacity rather than coverage
Solution Approach 1:
The system performs preliminary actions by predicting future cellular signal strength along user travel paths and proactively scheduling calls and data transfers during time intervals when strong signal is anticipated, preventing connection issues before they occur
Solution Approach 2:
The system enables user devices to autonomously monitor their own cellular signal strength along intended travel paths and self-schedule their communications during optimal signal conditions without requiring network operator intervention
2Ease of operation
If users make calls during travel, then communication needs are met, but dropped calls occur due to varying signal strength along the travel path
Solution Approach 1:
The system predicts cellular signal strength along the user's intended travel path in advance and schedules calls during specific time intervals when strong signal is anticipated, ensuring call stability before the call actually occurs
Solution Approach 2:
The system continuously monitors actual cellular signal strength during travel and uses this feedback to dynamically adjust and reschedule calls to optimal time intervals, improving call reliability through real-time adaptation
3Productivity
If data transfers are conducted during travel, then data needs are fulfilled, but connections drop due to bandwidth saturation in high-density areas
Solution Approach 1:
The system predicts future cellular signal strength and proactively schedules data transfers during time intervals when strong signal and available bandwidth are anticipated, preventing connection drops before they occur
Solution Approach 2:
The system dynamically adjusts data transfer scheduling based on real-time cellular signal strength monitoring and changing network conditions along the travel path, optimizing data transfer timing to maintain connection stability
Data Source
AI summary
In an approach to determining and scheduling future data transfers, one or more computer processors determine one or more future data transfers. The one or more computer processors identify an intended travel path of a user over a time interval. The one or more computer processors predict a network signal strength of a user device for the intended travel path over the time interval. The one or more computer processors schedule the one or more future data transfers during the time interval based on the predicted network signal strength.