An intelligent safety belt monitoring system, method and device based on asymmetric sampling and multi-dimensional state recognition

Abstract

This invention discloses an intelligent seatbelt monitoring system, method, and device based on asymmetric sampling and multi-dimensional state recognition. The system includes a main control unit and a connected monitoring module. The main control unit collects a first air pressure sequence at a first frequency, while the connected module collects a second air pressure sequence with timestamps or sequence numbers at a lower second frequency. The main control unit performs time-series resampling based on the timestamps or sequence numbers, aligning the second air pressure sampling points with the first air pressure sampling points on the time axis, and then calculates the relative altitude difference sequence between the two. This is combined with an altitude fluctuation amplitude feature model to identify abnormal states. This invention reduces power consumption in multi-node networking, overcomes timing misalignment errors caused by wireless packet loss, and independently identifies the state of each module under dynamic operating conditions and reduces the false alarm rate by extracting alternating fluctuation features and environmental interference shielding logic. It is suitable for retrofit deployment of safety equipment.

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