Expressway electromechanical operation and maintenance management method based on time series data of Internet of Things

By selectively decoding and constructing pattern constraint profiles, the problem of high computational resource consumption in data analysis of highway IoT monitoring terminals has been solved, and efficient and reliable abnormal target monitoring has been achieved.

CN121564665AActive Publication Date: 2026-02-24CHINA MERCHANTS XINZHI TECH CO LTD +1
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Patent Information

Application Number
CN202610090597.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-23
Publication Date
2026-02-24
Estimated Expiration
2046-01-23

AI Technical Summary

Technical Problem

In existing technologies, data analysis of highway IoT monitoring terminals is affected by background interference such as changes in lighting and weather, resulting in huge consumption of computing resources and poor detection efficiency and reliability.

Method used

By selectively decoding the encoded data stream of IoT terminals, marking background interference frames, constructing a pattern constraint profile, identifying abnormal encoded data based on encoding index constraints, adaptive monitoring, and reducing computing resource consumption.

Benefits of technology

It improves monitoring efficiency and reliability, reduces computing resource consumption, and enhances the accuracy of analysis of abnormal targets.

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Abstract

The invention relates to the field of Internet of Things terminal management, in particular to a highway electromechanical operation and maintenance management method based on Internet of Things time series data, which comprises the following steps of: selectively decoding a coded data stream, and marking background interference frames according to a plurality of decoded frames so as to analyze the influence of background interference on coded data; the method comprises the steps of setting an interference identifier for coded data of an observation time domain segment, identifying abnormal coded data for unidentified coded data, synchronously determining a target reference time domain segment where the abnormal coded data is located, decoding coded data in the target reference time domain segment, obtaining a plurality of reference frames, and processing the reference frames. According to the method, the difference of the coded data collected by the Internet of Things terminals is considered, the rule constraint portraits aiming at different Internet of Things terminals are constructed, the multi-dimensional coded data are monitored adaptively, on the premise of ensuring the reliability, only partial decoding is carried out, and when the method is oriented to the large-range Internet of Things terminals, the computing resource consumption is reduced, and the monitoring efficiency is improved.
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