Tracking Device Broadcast Reconfiguration for Longer Battery Life
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Solution Overview
Problem
Traditional tracking devices suffer from limited battery life due to unnecessary battery drain during periods of inactivity, such as when a user is sleeping, which reduces their operational time.
Innovation Solution
A tracking device is dynamically reconfigured based on diagnostic information to optimize power consumption, ensuring it operates for a predetermined threshold period by adjusting parameters like broadcast frequency and component settings, using a mobile device and a tracking system to manage power consumption models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional tracking devices broadcast advertisement packets at a predetermined frequency, then location tracking reliability is maintained, but battery life is unnecessarily reduced during periods of inactivity
Solution Approach 1:
The tracking device dynamically adjusts its broadcast frequency based on detected usage patterns and activity levels. During periods of inactivity (such as when the user is sleeping), the device reduces broadcast frequency to extend battery life, while maintaining higher frequency during active periods to ensure location tracking reliability. This dynamic adaptation resolves the contradiction by allowing the system to optimize between reliability and battery life based on real-time conditions.
Solution Approach 2:
The system changes the operational parameter of advertisement packet broadcast frequency based on diagnostic information about usage patterns. By modifying this key parameter dynamically - reducing frequency during inactivity and increasing it during active use - the system extends battery life without compromising tracking reliability when needed, directly addressing the technical contradiction.
2Reliability
If tracking devices provide frequent status updates to ensure continuous operation, then operational reliability is improved, but power consumption increases
Solution Approach 1:
The tracking device uses feedback from diagnostic information about its actual usage patterns and power consumption to adjust its operational behavior. By continuously monitoring how the device is used and comparing it against expected patterns, the system receives feedback that enables it to optimize the frequency of status updates, ensuring operational reliability while minimizing unnecessary power consumption during inactive periods.
Solution Approach 2:
The system performs preliminary analysis of usage patterns and diagnostic information to predict future power consumption trends. By anticipating when the user will be inactive or active, the device can proactively adjust its update frequency in advance, ensuring reliable operation during needed periods while reducing power consumption during predictable inactive periods.
Data Source
AI summary
A method includes determining, based on data obtained by one or more motion sensors of a tracking device, historical usage information that indicates a historical movement pattern of the tracking device and determining, based on the historical movement pattern of the tracking device, a length of time the tracking device can continue to operate. In response to determining that the length of time does not satisfy a predetermined threshold length of time, the method further includes generating reconfiguration instructions configured to cause the tracking device to adjust a broadcasting frequency of advertisement packets to extend the length of time the tracking device can continue to operate and transmitting the reconfiguration instructions to a user computing device associated with the tracking device, wherein the user computing device is configured to provide the reconfiguration instructions to the tracking device.