Abstract: In the field of home fire monitoring, the currently relatively mature monitoring solutions include GPRS/GSM com-munication and Zigbee communication. The main disadvantage of GPRS wireless communication is high power consumption, and the disadvantage of Zigbee technology is that it needs to be combined with other communication technologies to realize remote monitoring. In addition, the above technical solutions all require self-built local or remote monitoring servers to save mon-itoring data. In view of the above problems, this system designs a home fire monitoring system based on NB-IoT technology and cloud platform. The system uses a single-chip STM32F103C8T6 as the core controller and contains a sensor data acquisition module and a narrowband IoT communication module. The data fusion of multi-sensor data is performed by BP neural network algorithm.On the basis of remote transmission, the system solves the problems of high power consumption, high cost and insufficient signal coverage of terminal hardware. The system can collect indoor environmental parameters and fire information in real time, and upload them to the cloud platform for storage. If abnormal data is detected, an early warning message will be issued. The feasibility of the system is verified, and the verification results show that the system works normally and the output is accurate, which meets the design requirements and can be widely used.

Jun Wang, Ting Ke, Mengjie Hou and Gangyu Hu, “The Design of Home Fire Monitoring System based on NB-IoT” International Journal of Advanced Computer Science and Applications(IJACSA), 13(5), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130506

@article{Wang2022,
title = {The Design of Home Fire Monitoring System based on NB-IoT},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130506},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130506},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {Jun Wang and Ting Ke and Mengjie Hou and Gangyu Hu}
}