Wireless Asset Tracking via Dynamic Heartbeat Frequency Control
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Solution Overview
Problem
In fast-paced environments like hospitals, asset tracking faces challenges in optimizing power usage and accurate data collection due to assets being moved quickly and unpredictably, with existing tracking devices struggling to provide timely and precise location information.
Innovation Solution
A wireless sensing system that deploys gateway nodes to detect assets moving through gates and uses machine learned models to determine direction of movement, adjusting the frequency of heartbeat signals from tape nodes based on signal strength and location, ensuring efficient battery life and accurate tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the frequency of heartbeat signals is increased to accommodate fast-moving assets, then tracking accuracy is improved, but battery life is drained
Solution Approach 1:
The system dynamically adjusts the heartbeat signal frequency based on the asset's movement state. When an asset is detected to be in motion (through gateway node signal strength changes), the heartbeat frequency increases to capture tracking data. When the asset is stationary, the frequency decreases to conserve battery power. This dynamic adaptation resolves the contradiction between tracking accuracy and energy consumption.
Solution Approach 2:
The system changes the parameter of heartbeat signal frequency based on operational conditions. The frequency is not fixed but varies according to whether the asset is moving or stationary, allowing the system to optimize between measurement precision and energy usage by adjusting this key parameter in response to environmental conditions.
2Loss of information
If the frequency of heartbeat signals is increased to track fast-moving assets, then data collection accuracy is improved, but power consumption increases
Solution Approach 1:
The system implements dynamic frequency adjustment where heartbeat signals are transmitted at high frequency only when movement is detected by gateway nodes. When assets are stationary, the frequency drops to minimal intervals. This dynamic behavior ensures data collection accuracy is maintained during movement while minimizing power consumption during stationary periods.
Solution Approach 2:
The system uses periodic heartbeat signals with variable intervals rather than continuous transmission. The periodic nature allows the system to collect necessary tracking data at appropriate moments while leaving gaps for energy conservation, particularly when assets are not in motion.
3Reliability
If gateway nodes are deployed throughout a building to detect movement through gates, then tracking reliability is improved, but device complexity increases
Solution Approach 1:
The system segments the tracking function by deploying distributed gateway nodes at strategic locations (entrances, exits, key areas) rather than requiring continuous coverage throughout the entire building. Each gateway node independently monitors its local area and reports to the central system, achieving reliable tracking through coordinated segmentation of the monitoring space.
Solution Approach 2:
Gateway nodes serve as intermediary devices between the central tracking system and moving assets. They receive heartbeat signals from assets, determine movement status through signal strength analysis, and relay this information to the central system. This intermediary layer simplifies the overall architecture by distributing intelligence to strategic points rather than requiring complex centralized processing for every asset.
Data Source
AI summary
A method for tracking assets in areas of interest includes receiving, by a first node of a wireless sensing system, a first communication and a second communication by a tape node associated with a mobile asset and receiving, by a second node of the wireless sensing system, the first communication and the second communication by the tape node associated with the mobile asset. A direction of movement of the tape node associated with the mobile asset is computed, the direction of movement based at least in part on respective signal strengths of the first communication and the second communication as received by the first node and the second node. Based on the direction of movement, a most likely path of the tape node is determined.