| Peer-Reviewed

Design and Evaluation Method of Wireless Fire Detection Node Based on Multi-source Sensor Data Fusion

Received: 17 January 2021     Accepted: 25 January 2021     Published: 30 January 2021
Views:       Downloads:
Abstract

In view of the problem that the traditional fire detection node is not intelligent enough for data processing when building fire occurs, a design and evaluation method of wireless fire detection node based on multi-source sensor data fusion is proposed. Firstly, the temperature and humidity sensor, carbon monoxide sensor and smoke sensor are selected to collect three kinds of fire information eigenvalues at the same time. Secondly, the analysis and processing method of two-level data fusion is established, and the fire information is processed in STC89C52 microcontroller. The first level data fusion uses fuzzy proximity algorithm to get the eigenvectors of environmental parameters, so that the measured values are closer. The second level data fusion uses D-S evidence theory to analyze the data systematically. According to the probability distribution function after fusion, more accurate decision results are obtained. Finally, the fire signal is sent to the superior data management center through ZigBee wireless transmission network, and the alarm signal is triggered in time. The whole node design gives a complete hardware selection and software data fusion processing method. Compared with the traditional fire detection node, it significantly reduces the false alarm rate. At the same time, the node has good application effect in the experiment, and realizes a wireless intelligent fire detection node with low cost, wide application range and high intelligence.

Published in International Journal of Sensors and Sensor Networks (Volume 9, Issue 1)
DOI 10.11648/j.ijssn.20210901.13
Page(s) 19-24
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Fire Detection, Two Level Data Fusion, Fuzzy Proximity Algorithm, D-S Evidence Theory

References
[1] Luo Xiaoquan, pan Shanliang, Fire alarm system based on multi-sensor data fusion [J]. Data communication, 2019 (06): 22-26, 31
[2] Xufeng Wei, Yahui Wang and Yanliang Dong, "Design of fire detection system in buildings based on wireless multimedia sensor networks," Proceeding of the 11th World Congress on Intelligent Control and Automation, Shenyang, 2014, pp. 3008-3012.
[3] Zhang Bohu, Chen Jianli. Design of fire detection system based on artificial intelligence technology and ZigBee [J]. Fire science and technology, 2008 (01): 49-51
[4] Ning Du, Zhi Long Liu, Huai Guo Dong. Design of Wireless Sensor Network for Fire Detection [J]. 2014, 3265: 657-660.
[5] S. Liu, D. Tu and Y. Zhang, "Multiparameter fire detection based on wireless sensor network," 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, Shanghai, 2009, pp. 203-206.
[6] Zeng Sitong, Tong Xiaowei, Shen peihui. Design of fire detection system based on wireless multi-sensor information fusion [J]. Journal of Hubei Institute of technology, 2019, 35 (06): 23-27, 32.
[7] Liu Yan, "The reasearch to the signal transmission for fire detector," 2011 International Conference on Electric Information and Control Engineering, Wuhan, 2011, pp. 855-858.
[8] He-zhi Guo, Jun-ling Gao and Ben-yu Huang, "Apply of coal-bunker fire warning system based on ZigBee," 2014 IEEE Workshop on Electronics, Computer and Applications, Ottawa, ON, 2014, pp. 376-378.
[9] Ding min. design of wireless intelligent automatic fire alarm system [J]. New technology and new products in China, 2019 (14): 143-144
[10] Cheng Wenbin, Du Lei, Liu Yiyi. Design of home fire detection system based on wireless multi-sensor data fusion [J]. Telecom Science, 2017, 33 (09): 174-181
[11] Chen Quan. Design of intelligent fire alarm based on 51 MCU [J]. Electronic production, 2017 (23): 25-28
[12] Zhang Qiang, Zhang Chaolong, Li Nan, Jiang Shanhe, Li Yanmei. Design of intelligent fire alarm based on MCU [J]. Computer knowledge and technology, 2019, 15 (12): 210-212.
[13] Wu Jinghong, Wu Jinghong, Liu Xun. Design of coal mine safety monitoring system based on ZigBee technology and information fusion [J]. Coal engineering, 2017, 49 (10): 55-58, 62
[14] S. Tian and M. Kou, "Fire Safety Assessment of an Underground Parking Area Based on D-S Evidence Theory," 2014 7th International Conference on Intelligent Computation Technology and Automation, Changsha, 2014, pp. 268-271.
[15] Luo Xiaoquan, pan Shanliang. Application Research of multisensor data fusion in fire detection [J]. Wireless communication technology, 2019, 28 (03): 57-62
Cite This Article
  • APA Style

    Huang Ye, Wang Xiaogang, Gan Shuchuan. (2021). Design and Evaluation Method of Wireless Fire Detection Node Based on Multi-source Sensor Data Fusion. International Journal of Sensors and Sensor Networks, 9(1), 19-24. https://doi.org/10.11648/j.ijssn.20210901.13

    Copy | Download

    ACS Style

    Huang Ye; Wang Xiaogang; Gan Shuchuan. Design and Evaluation Method of Wireless Fire Detection Node Based on Multi-source Sensor Data Fusion. Int. J. Sens. Sens. Netw. 2021, 9(1), 19-24. doi: 10.11648/j.ijssn.20210901.13

    Copy | Download

    AMA Style

    Huang Ye, Wang Xiaogang, Gan Shuchuan. Design and Evaluation Method of Wireless Fire Detection Node Based on Multi-source Sensor Data Fusion. Int J Sens Sens Netw. 2021;9(1):19-24. doi: 10.11648/j.ijssn.20210901.13

    Copy | Download

  • @article{10.11648/j.ijssn.20210901.13,
      author = {Huang Ye and Wang Xiaogang and Gan Shuchuan},
      title = {Design and Evaluation Method of Wireless Fire Detection Node Based on Multi-source Sensor Data Fusion},
      journal = {International Journal of Sensors and Sensor Networks},
      volume = {9},
      number = {1},
      pages = {19-24},
      doi = {10.11648/j.ijssn.20210901.13},
      url = {https://doi.org/10.11648/j.ijssn.20210901.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20210901.13},
      abstract = {In view of the problem that the traditional fire detection node is not intelligent enough for data processing when building fire occurs, a design and evaluation method of wireless fire detection node based on multi-source sensor data fusion is proposed. Firstly, the temperature and humidity sensor, carbon monoxide sensor and smoke sensor are selected to collect three kinds of fire information eigenvalues at the same time. Secondly, the analysis and processing method of two-level data fusion is established, and the fire information is processed in STC89C52 microcontroller. The first level data fusion uses fuzzy proximity algorithm to get the eigenvectors of environmental parameters, so that the measured values are closer. The second level data fusion uses D-S evidence theory to analyze the data systematically. According to the probability distribution function after fusion, more accurate decision results are obtained. Finally, the fire signal is sent to the superior data management center through ZigBee wireless transmission network, and the alarm signal is triggered in time. The whole node design gives a complete hardware selection and software data fusion processing method. Compared with the traditional fire detection node, it significantly reduces the false alarm rate. At the same time, the node has good application effect in the experiment, and realizes a wireless intelligent fire detection node with low cost, wide application range and high intelligence.},
     year = {2021}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Design and Evaluation Method of Wireless Fire Detection Node Based on Multi-source Sensor Data Fusion
    AU  - Huang Ye
    AU  - Wang Xiaogang
    AU  - Gan Shuchuan
    Y1  - 2021/01/30
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ijssn.20210901.13
    DO  - 10.11648/j.ijssn.20210901.13
    T2  - International Journal of Sensors and Sensor Networks
    JF  - International Journal of Sensors and Sensor Networks
    JO  - International Journal of Sensors and Sensor Networks
    SP  - 19
    EP  - 24
    PB  - Science Publishing Group
    SN  - 2329-1788
    UR  - https://doi.org/10.11648/j.ijssn.20210901.13
    AB  - In view of the problem that the traditional fire detection node is not intelligent enough for data processing when building fire occurs, a design and evaluation method of wireless fire detection node based on multi-source sensor data fusion is proposed. Firstly, the temperature and humidity sensor, carbon monoxide sensor and smoke sensor are selected to collect three kinds of fire information eigenvalues at the same time. Secondly, the analysis and processing method of two-level data fusion is established, and the fire information is processed in STC89C52 microcontroller. The first level data fusion uses fuzzy proximity algorithm to get the eigenvectors of environmental parameters, so that the measured values are closer. The second level data fusion uses D-S evidence theory to analyze the data systematically. According to the probability distribution function after fusion, more accurate decision results are obtained. Finally, the fire signal is sent to the superior data management center through ZigBee wireless transmission network, and the alarm signal is triggered in time. The whole node design gives a complete hardware selection and software data fusion processing method. Compared with the traditional fire detection node, it significantly reduces the false alarm rate. At the same time, the node has good application effect in the experiment, and realizes a wireless intelligent fire detection node with low cost, wide application range and high intelligence.
    VL  - 9
    IS  - 1
    ER  - 

    Copy | Download

Author Information
  • School of Automation & Information Engineering, Sichuan University of Science & Engineering, Yibin, China

  • School of Automation & Information Engineering, Sichuan University of Science & Engineering, Yibin, China

  • School of Automation & Information Engineering, Sichuan University of Science & Engineering, Yibin, China

  • Sections