Iot-based pallet dynamic tracking method and device

By working collaboratively with edge nodes and the cloud, tray sensing data is acquired using RFID readers and Bluetooth positioning base stations. Confidence calculations are performed to measure signal strength and stability. Combined with weighted fusion of spatiotemporal feature vectors and state classification, motion state markers are generated, and a reliable trajectory generation strategy is constructed. This solves the problems of inaccurate positioning and incomplete trajectory recording in tray tracking, achieving accurate and continuous improvement in tray tracking.

CN122020267BActive Publication Date: 2026-07-07ZHEJIANG JIUDING SUPPLY CHAIN MANAGEMENT CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG JIUDING SUPPLY CHAIN MANAGEMENT CO LTD
Filing Date
2026-04-14
Publication Date
2026-07-07

AI Technical Summary

Technical Problem

Existing pallet tracking systems are inadequate in data acquisition and signal processing, lacking a sound motion determination mechanism and trajectory generation strategy, resulting in inaccurate positioning and unsatisfactory trajectory recording accuracy, making it difficult to achieve efficient trajectory completion.

Method used

By working collaboratively between edge nodes and the cloud, tray perception data is acquired using RFID readers and Bluetooth positioning base stations. Confidence calculations are performed on signal strength thresholds and historical stability metrics. Combined with weighted fusion of spatiotemporal feature vectors and state classification, motion state markers are generated, a reliable trajectory generation strategy is constructed, and trajectory recording is optimized through breakpoint detection and probability filling.

Benefits of technology

It achieves accurate acquisition of pallet positioning, builds a reliable trajectory generation mechanism, ensures continuous improvement and accuracy of pallet tracking, and solves the shortcomings of traditional technologies in data acquisition, status recognition and trajectory processing.

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Abstract

The embodiment of the application provides a tray dynamic tracking method and device based on Internet of Things, and the accurate acquisition of positioning is realized through signal fusion and confidence degree calculation. A tracking mechanism is constructed, state classification and window adjustment are combined, and a reliable trajectory generation strategy is established. Trajectory optimization is introduced, and through breakpoint detection and probability filling, continuous improvement of tracking is ensured. The method effectively solves the deficiencies of traditional technologies in data acquisition, state recognition and trajectory processing, and provides technical support for tray tracking.
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