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An Intelligent Elevator System Based on Low Power Wireless Networks

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6GN for Future Wireless Networks (6GN 2020)

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Abstract

The trend of Internet of Things (IoT) and wireless network techniques have resulted in a promising paradigm, and a more rational and intelligent elevator control system shall be considered. Many previous works are devoted to improving traffic congestion capability to increase time efficiency. However, these approaches confront the limitations of destination perception in advance or there is a steady stream of persons coming to wait the elevator that may increase the uncertainty of sensing the traffic load, since the user interface is still around elevator car. In this paper, an improved elevator system is proposed with remote calling and cloud scheduling based on low power wireless networks. It enables users to call the elevator remotely through portable devices, solves the problem of elevator invalid stop, reduces system energy consumption, and improves the service life of the elevator. It can match the running state of the elevator with the multi-user call request, shorten the time for users to take the elevator, and improve the comprehensive operation efficiency of the elevator.

Sponsored by the Young Innovative Project from Guangdong Province of China (No. 2018KQNCX403) and the Teaching Reform Project from Shenzhen Technology University (No. 2018105101002).

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Authors and Affiliations

  1. College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China

    Congying Yu, Ruize Sun, Qijun Hong, Weiwen Chao & Lei Ning

Authors
  1. Congying Yu
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  2. Ruize Sun
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  3. Qijun Hong
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  4. Weiwen Chao
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  5. Lei Ning
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Corresponding author

Correspondence to Lei Ning .

Editor information

Editors and Affiliations

  1. College of Intelligence and Computing, Tianjin University, Tianjin, Tianjin, China

    Xiaofei Wang

  2. Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada

    Victor C. M. Leung

  3. School of Computer Science and Technology, Tianjin University, Tianjin, Tianjin, China

    Keqiu Li

  4. University of Science and Technology, Beijing, China

    Haijun Zhang

  5. Shenzhen University, Shenzhen, China

    Xiping Hu

  6. National University of Defense Technology, Changsha, China

    Qiang Liu

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Yu, C., Sun, R., Hong, Q., Chao, W., Ning, L. (2020). An Intelligent Elevator System Based on Low Power Wireless Networks. In: Wang, X., Leung, V.C.M., Li, K., Zhang, H., Hu, X., Liu, Q. (eds) 6GN for Future Wireless Networks. 6GN 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-030-63941-9_19

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  • DOI: https://doi.org/10.1007/978-3-030-63941-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-63940-2

  • Online ISBN: 978-3-030-63941-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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