Abstract
Since the reform and opening up, China’s economy has been rapidly developed, people in the face of constantly improving living standards and increasing work pressure, their health consciousness is more and more strong, fitness exercise is more and more accepted, more and more people began to pay attention to the exercise in the work. In order to meet this market demand, the number of health clubs has mushroomed, but along with the number of health club fires has risen sharply. The development of Internet of things technology has provided a new way to prevent and reduce the occurrence of fire in fitness clubs, and helped a new way of fire induction and early warning. Emerging Internet of things technology based fire induction system of computer network and sensor network in a particular area, such as the combined effectively, so effectively improved the fitness club these traffic large place fire alarm system, monitoring means, greatly improved the timeliness and reliability of the automatic fire pre-alarm system, at the same time to the fitness club this kind of foot traffic place fire prevention management with the help of modern technology becomes simple and efficient, also make the management more diversified.
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References
Liu, Y., Pang, L.X., Liang, J.: A compact solid-state UV flame sensing system based on wide-gap II—VI thin film materials. IEEE Trans. Industr. Electron. 42(26), 7–15 (2018)
Li, G.H., Han, W.P., Guo, G., et al.: Influencing factors on the actuation time of the thermal release mechanism with temperature sensing element of fire rolling shutters. Procedia Eng. 211(15), 353–357 (2018). Implantable tissue perfusion sensing system and method
Usak, M., Kubiatko, M., Shabbir, M.S.: Health care service delivery based on the Internet of things: a systematic and comprehensive study. Int. J. Commun. Syst. 6(7), 3–8 (2019)
Li, X., Zhao, N., Jin, R.: Internet of Things to network smart devices for ecosystem monitoring. Sci. Bull. 64(17), 1234–1245 (2019)
Mayer, M., Baeumner, A.J.: A megatrend challenging analytical chemistry: biosensor and chemosensor concepts ready for the internet of things. Chem. Rev. 119(13), 37–42 (2019)
Qiao, C., Wu, L., Chen, T.: Study on forest fire spreading model based on remote sensing and GIS. In: IOP Conference Series Earth and Environmental Science, vol. 199, no. 59, pp. 220–237 (2018)
Zhong, D., Shi, M., Cui, B.: Research progress of the intelligent construction of dams. Shuili Xuebao/J. Hydraul. Eng. 50(1), 38–52 (2019)
Fonollosa, J., Solórzano, A.: Chemical sensor systems and associated algorithms for fire detection: a review. Sensors 18(2), 553 (2018)
Bhuiyan, M.Z.A., Wu, J., Wang, G.: e-sampling: event-sensitive autonomous adaptive sensing and low-cost monitoring in networked sensing systems. ACM Trans. Auton. Adapt. Syst. 12(1), 1–29 (2017)
Li, Y., Huang, Y., Zhang, M.: Service selection mechanisms in the Internet of Things (IoT): a systematic and comprehensive study. Cluster Comput. 8(3), 1–21 (2019)
Parry, J.R.: Primal weaving: structure and meaning in language and architecture. Substance 946(855), 1039–1051 (2017)
Wang, F., Zhang, Y., Wang, W.: Development of a multi-perimeter sensing system based on POTDR. IEEE Photonics J. 54(93), 41–61 (2018)
Yan, S., Shi, K., Li, Y.: Integration of satellite remote sensing data in underground coal fire detection: a case study of the Fukang region, Xinjiang. China. Front. Earth Sci. 83(114), 90–94 (2019)
Lin, Z., Chen, F., Niu, Z.: An active fire detection algorithm based on multi-temporal FengYun-3C VIRR data. Remote Sens. Environ. 211(15), 328–341 (2018)
Leiva, J.N., Robbins, J., Saraswat, D.: Evaluating remotely sensed plant count accuracy with differing unmanned aircraft system altitudes, physical canopy separations, and ground covers. J. Appl. Remote Sens. 11(3), 36–43 (2017)
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The 13th five year social science project of Jilin Provincial Department of Education, JJKH20190781SK.
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Sun, J. (2020). Design and Development of the Fire Sensor System of Fitness Club Based on the Internet of Things. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1146. Springer, Cham. https://doi.org/10.1007/978-3-030-43306-2_87
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DOI: https://doi.org/10.1007/978-3-030-43306-2_87
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