Research and Application of Hazardous Chemicals Monitoring Technology Based on Big Data and Patrol Robot

Aiming at the characteristics of small monitoring range and low alarm accuracy in the traditional fixed monitor of hazardous chemicals warehouse, a patrol robot of hazardous chemicals warehouse is studied. A multi-sensor data fusion method based on laida criterion to improve the fusion performance o...

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Bibliographic Details
Published in2022 2nd Asia Conference on Information Engineering (ACIE) pp. 5 - 9
Main Authors An, Qing, Chen, Xijiang, Liu, Fenggang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2022
Subjects
Couplings
Data fusion
Data integration
Humidity
multisensor
neural network
Neural networks
robot
Temperature distribution
Temperature measurement
Temperature sensors
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DOI10.1109/ACIE55485.2022.00009

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Summary:Aiming at the characteristics of small monitoring range and low alarm accuracy in the traditional fixed monitor of hazardous chemicals warehouse, a patrol robot of hazardous chemicals warehouse is studied. A multi-sensor data fusion method based on laida criterion to improve the fusion performance of BP neural network is adopted. By collecting the data such as the concentration of leaked hazardous chemicals, the ambient temperature and humidity in the warehouse, the data is denoised After normalization, BP neural network is used for fusion output. The prototype test results show that this method can effectively improve the grasp of the space environment of the patrol robot in the dangerous chemical warehouse, greatly improve the accuracy and reliability of the alarm, and have good sensor scalability.
DOI:10.1109/ACIE55485.2022.00009