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A Real-Time Location-Based Services System Using WiFi Fingerprinting Algorithm for Safety Risk Assessment of Workers in Tunnels

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  • Peng Lin
  • Qingbin Li
  • Qixiang Fan
  • Xiangyou Gao
  • Senying Hu

Abstract

This paper investigates the feasibility of a real-time tunnel location-based services (LBS) system to provide workers’ safety protection and various services in concrete dam site. In this study, received signal strength- (RSS-) based location using fingerprinting algorithm and artificial neural network (ANN) risk assessment is employed for position analysis. This tunnel LBS system achieves an online, real-time, intelligent tracking identification feature, and the on-site running system has many functions such as worker emergency call, track history, and location query. Based on ANN with a strong nonlinear mapping, and large-scale parallel processing capabilities, proposed LBS system is effective to evaluate the risk management on worker safety. The field implementation shows that the proposed location algorithm is reliable and accurate (3 to 5 meters) enough for providing real-time positioning service. The proposed LBS system is demonstrated and firstly applied to the second largest hydropower project in the world, to track workers on tunnel site and assure their safety. The results show that the system is simple and easily deployed.

Suggested Citation

  • Peng Lin & Qingbin Li & Qixiang Fan & Xiangyou Gao & Senying Hu, 2014. "A Real-Time Location-Based Services System Using WiFi Fingerprinting Algorithm for Safety Risk Assessment of Workers in Tunnels," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, April.
    • Handle: RePEc:hin:jnlmpe:371456
    DOI: 10.1155/2014/371456
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    Cited by:

    1. Xiaoming Yuan & Yueqi Bi & Mingrui Hao & Qiang Ji & Zhigeng Liu & Jiusheng Bao, 2022. "Research on Location Estimation for Coal Tunnel Vehicle Based on Ultra-Wide Band Equipment," Energies, MDPI, vol. 15(22), pages 1-17, November.
    2. Arso M. Vukićević & Ivan Mačužić & Marko Djapan & Vladimir Milićević & Luiza Shamina, 2021. "Digital Training and Advanced Learning in Occupational Safety and Health Based on Modern and Affordable Technologies," Sustainability, MDPI, vol. 13(24), pages 1-13, December.
    3. Antonella Pireddu & Angelico Bedini & Mara Lombardi & Angelo L. C. Ciribini & Davide Berardi, 2024. "A Review of Data Mining Strategies by Data Type, with a Focus on Construction Processes and Health and Safety Management," IJERPH, MDPI, vol. 21(7), pages 1-26, June.

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