Tracker Cluster Power Management via Sleep State Rotation
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Solution Overview
Problem
Current trackers face a trade-off between size reduction and extended running time due to the capacity and volume relationship of batteries, lacking a solution that maintains long battery life while being compact.
Innovation Solution
A tracker system with a positioning circuit, remote communication circuit, and processing circuit that operates in default and cluster modes, where the processing circuit controls the tracker to enter working or sleep states based on received cluster commands, optimizing power usage by designating only one tracker to actively report position information within a cluster, thereby extending battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If a battery with larger capacity is used to extend running time, then the running time is improved, but the volume of the tracker increases
Solution Approach 1:
The tracker implements periodic action by alternating between working state and sleep state. The processing circuit controls the tracker to enter working state during working time periods and sleep state during rest periods, as specified by cluster commands from the cloud server. This periodic operation reduces average power consumption, enabling extended running time with smaller capacity batteries.
Solution Approach 2:
The tracker employs dynamic state adjustment by transitioning between different operational modes (default mode and cluster mode) and states (working state and sleep state). The processing circuit dynamically changes the operational state based on received cluster commands, optimizing power consumption according to actual tracking needs and environmental conditions.
2Measurement precision
If all trackers in a cluster continuously report position information, then tracking accuracy is improved, but power consumption increases
Solution Approach 1:
The system implements partial action by having only one tracker (the first tracker) actively report position information to the cloud server, while other trackers (second trackers) remain in sleep state. This partial participation approach maintains adequate tracking accuracy through the representative tracker while significantly reducing overall power consumption of the cluster.
Solution Approach 2:
The cloud server performs automatic classification of trackers into clusters based on position information and automatically assigns roles (first tracker or second tracker) without manual intervention. The system self-manages the distribution of reporting responsibilities, optimizing power consumption while maintaining tracking effectiveness.
Data Source
AI summary
A clustered tracking system includes a plurality of trackers and a cloud server. Each of trackers includes a remote communication circuit, a positioning circuit and a processing circuit. The positioning circuit obtains a position information. The cloud server respectively receives a plurality of identity information and a plurality of position information from a plurality of the remote communication circuits, and classifies the trackers being adjacent to each other into a tracked cluster according to the identity information and the position information, and transmits a cluster command to the tracked cluster. The trackers in the tracked cluster are divided into a first tracker and at least one second tracker. The first tracker enters a working state in a working time period according to the cluster command. The second tracker enters a sleep state according to the cluster command.