Research and Design of an Intelligent IoT Monitoring System for Coal Mine Gas Based on the Fuzzy-PID Algorithm

—To enhance the safety and efficiency of coal mine gas monitoring, this study develops an intelligent Internet of Things (IoT) monitoring system incorporating a Fuzzy-PID control algorithm. The system is structured into four layers—sensing, network transmission, control service, and mobile applicati...

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Vydáno v:International journal of advanced network, monitoring, and controls Ročník 10; číslo 1; s. 11 - 28
Hlavní autoři: Yang, Shengquan, Zhang, Jun, Zhang, Zhengxin, Ji, Ruixin
Médium: Journal Article
Jazyk:angličtina
Vydáno: Xi'an Sciendo 01.01.2025
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Témata:
Coal Mine Gas
Coal mining
Communication
Control algorithms
Data analysis
Data encryption
Data transmission
Energy consumption
Fuzzy logic
Fuzzy PID
Gas monitoring
Humidity
Internet of Things
Mines
Mining accidents & safety
Mining industry
Monitoring System
Monitoring systems
Sensors
Ventilation
ISSN:2470-8038, 2470-8038
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Shrnutí:—To enhance the safety and efficiency of coal mine gas monitoring, this study develops an intelligent Internet of Things (IoT) monitoring system incorporating a Fuzzy-PID control algorithm. The system is structured into four layers—sensing, network transmission, control service, and mobile application— ensuring real-time data acquisition, stable transmission, intelligent processing, and remote monitoring. The Fuzzy-PID algorithm dynamically adjusts control parameters to improve response time and accuracy under nonlinear and uncertain conditions. Simulation experiments validate the system's performance, comparing traditional PID, Fuzzy, and Fuzzy-PID control strategies. Results indicate that the traditional PID algorithm achieves a response time of 2.0 s but exhibits oscillations of ±0.1 concentration units. The Fuzzy control algorithm stabilizes gas concentration within 4.0 s with deviations below ±0.05 units. The proposed Fuzzy-PID algorithm achieves an optimal balance, stabilizing gas concentration within 2.5 s with deviations reduced to less than ±0.03 units. These improvements enhance mine safety by reducing gas concentration fluctuations and providing real-time risk alerts. Practical deployment in a coal mining enterprise confirms the system’s capability in reducing manual intervention by 30% and improving early warning accuracy by 25%, demonstrating its potential for intelligent mine development.
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ISSN:2470-8038
2470-8038
DOI:10.2478/ijanmc-2025-0002