A method and system for locating multiple potential sources of toxic and harmful gases indoors

CN120668871BActive Publication Date: 2026-05-26UNIV OF SCI & TECH OF CHINA
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
UNIV OF SCI & TECH OF CHINA
Filing Date
2025-06-13
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies for tracing the source of toxic and harmful gases indoors suffer from poor sensor dependence, easy reading drift, and poor anti-interference capabilities. Existing technologies are difficult to quickly and accurately identify multiple potential sources, and the stability and anti-interference capabilities of the sensors are insufficient, failing to meet the multi-source positioning requirements of complex indoor environments.

Method used

By combining teaching and learning optimization algorithms with dynamic class assignment strategies, a system consisting of point-based source tracing units, spatial positioning units, and detection units is used to locate multiple potential sources using high-sensitivity in-situ detection instruments. This includes population initialization, liaison officer setting, dynamic class assignment, and multi-teacher teaching optimization, thereby achieving accurate identification of multiple indoor pollution sources.

Benefits of technology

It improves the success rate and positioning accuracy of multi-source tracing, breaks through the limitations of parameter dependence of traditional algorithms and the anti-interference ability of sensors, and realizes rapid and accurate identification and detection of multiple potential sources indoors.

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Abstract

This invention discloses a method and system for locating multiple potential sources of toxic and harmful gases indoors. The method includes: updating measurement points in a modeling space; introducing a dynamic class-based strategy to divide individuals within the space population into classes based on a teaching and learning optimization algorithm; updating individual positions by performing teaching and learning stages on each class; dynamically adjusting teaching factors to change teaching paths; designing individual value and changing learning paths; selecting elite individuals and introducing liaisons as global planners to inject individuals, replacing the worst individuals in the population; determining the updated position of each measurement point; modeling the indoor environment; receiving the updated positions and guiding the measurement points to move to the updated positions; detecting the concentration of toxic and harmful gases at the measurement points and feeding it back to the point-based source tracing unit for subsequent position updates. This improves the success rate and accuracy of multi-source tracing and addresses the shortcomings of current multi-source location methods in indoor environments.
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