A Smart Evaluation Method and System for Indoor Gas Safety Inspection Work Orders

By constructing a logical closed-loop verification mechanism in the spatiotemporal dimensions, and combining computer vision and semantic consistency verification, the problems of reusing old images and staging cross-household photos in gas safety inspections have been solved, enabling accurate identification and evaluation of the aging status of facilities and improving the credibility and accuracy of safety inspection data.

CN122135052APending Publication Date: 2026-06-02BOCOM SMART INFORMATION TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BOCOM SMART INFORMATION TECH CO LTD
Filing Date
2026-03-02
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing gas safety inspection systems are unable to effectively identify highly concealed violations and fraudulent activities, such as uploading old images for reuse or staging photos across different households. This makes it difficult to verify the authenticity and accuracy of safety inspections, and lacks the logical verification capabilities based on the time dimension and physical evolution patterns.

Method used

By introducing a physical state evolution model, a logical closed-loop verification mechanism based on spatiotemporal dimensions is constructed. Combining computer vision models and historical data, deep neural networks are used for target detection and defect segmentation, the natural aging rate of facilities is calculated, logical anomaly verification is performed based on spatiotemporal evolution laws, and intelligent evaluation results are generated by combining semantic consistency verification.

Benefits of technology

It enables in-depth spatiotemporal logic verification of security inspection photos, accurately identifies abnormal data that violates the laws of natural aging, improves the credibility and accuracy of security inspection data, ensures the objectivity and rigor of evaluation results, and adapts to changes in the aging rate of facilities under different environments.

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Abstract

This invention discloses an intelligent evaluation method and system for indoor gas safety inspection work orders, relating to the fields of computer data processing and artificial intelligence application technology. The method acquires the current image and timestamp of the inspection site and retrieves historical archived data from the same location. It uses a deep learning model to quantify and identify the current physical state value of the facility, constructs a spatiotemporal evolution model based on the natural aging rate and time interval, and calculates the theoretically predicted state value at the current moment. By comparing the actual state value with the theoretically predicted value, it determines whether there are logical anomalies that violate the principle of physical entropy increase or aging rate constraints. Finally, it combines the semantic consistency of the image and text to generate a comprehensive quality evaluation of the work order. This invention creatively introduces the constraints of physical laws in the time dimension, effectively solving the highly concealed data forgery problems such as "reusing old images" and "swapping," realizing automated auditing of the authenticity of safety inspection data, and significantly improving the intelligent level of urban gas safety management.
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