TY - GEN
T1 - The research of distributed CO2 monitoring technology based on NB-IoT
AU - Hu, Chun
AU - Li, Yanlin
AU - Zheng, Dezhi
AU - Cheng, Yufei
AU - Peng, Peng
AU - Nie, Sichong
N1 - Publisher Copyright:
© 2025 SPIE.
PY - 2025
Y1 - 2025
N2 - CO2 is one of the primary contributors to the greenhouse effect, and its monitoring and control are critical for achieving carbon peaking and neutrality goals. Therefore, large-scale distributed monitoring of CO2 concentrations in the environment is of significant importance. To investigate the diffusion patterns of CO2 in windless environments, this paper designs and implements a distributed CO2 monitoring system. The system adopts the three-layer architecture of the Internet of Things (IoT) as its overall framework, utilizing a self-developed CO2 sensor as the sensing layer node. The system employs the Narrowband Internet of Things (NB-IoT) protocol to achieve multi-node, wide-coverage, and low-power data transmission and reception. A custom database is developed as the application layer to store, classify, and manage data collected by the nodes. Experimental results provide CO2 monitoring data, which are analyzed to summarize the variation patterns of CO2 concentration over time and distance. By comparing these results with existing gas diffusion models, it is found that the trends are consistent, thereby demonstrating the reliability and stability of the proposed system.
AB - CO2 is one of the primary contributors to the greenhouse effect, and its monitoring and control are critical for achieving carbon peaking and neutrality goals. Therefore, large-scale distributed monitoring of CO2 concentrations in the environment is of significant importance. To investigate the diffusion patterns of CO2 in windless environments, this paper designs and implements a distributed CO2 monitoring system. The system adopts the three-layer architecture of the Internet of Things (IoT) as its overall framework, utilizing a self-developed CO2 sensor as the sensing layer node. The system employs the Narrowband Internet of Things (NB-IoT) protocol to achieve multi-node, wide-coverage, and low-power data transmission and reception. A custom database is developed as the application layer to store, classify, and manage data collected by the nodes. Experimental results provide CO2 monitoring data, which are analyzed to summarize the variation patterns of CO2 concentration over time and distance. By comparing these results with existing gas diffusion models, it is found that the trends are consistent, thereby demonstrating the reliability and stability of the proposed system.
KW - atmospheric pollution
KW - carbon dioxide (CO2) gas monitoring
KW - distributed system
KW - Narrowband Internet of Things technology
UR - http://www.scopus.com/inward/record.url?scp=105000123499&partnerID=8YFLogxK
U2 - 10.1117/12.3057324
DO - 10.1117/12.3057324
M3 - Conference contribution
AN - SCOPUS:105000123499
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Fourth International Computational Imaging Conference, CITA 2024
A2 - Shao, Xiaopeng
A2 - Shao, Xiaopeng
PB - SPIE
T2 - 4th International Computational Imaging Conference, CITA 2024
Y2 - 20 September 2024 through 22 September 2024
ER -