Indoor Disaster Detection and Real-Time Escape Guidance System

  • Authors

    • Dae-Yeon Noh
    • Yoon-Young Park
    • Kang-Hee Jung
    • Ho-Won Lee
    • Joong-Eup Kye
    https://doi.org/10.14419/ijet.v7i3.24.22688
  • Disaster, Indoor, Escape, Simulation, Detection.
  • Background/Objectives: When disasters occur in crowded indoor spaces, many property and human lives are lost. Simulate an indoor disaster escape system to minimize damage.

    Methods/Statistical analysis: Data measured by sensors or disaster robots are sent to middleware responsible for the area. Each middleware uses data to determine whether a disaster has occurred indoors. If a disaster occurs, locate victims of disaster and provide safe escape routes through pre-built maps. Through these methods, we simulate whether a disaster occurred and how well we can identify the escape route.

    Findings: BLE BEACON was used to locate victims of disaster. Later, he informed the victim of the shortest route to escape through middleware and servers. As a result, they were able to create indoor navigation with errors of about 3 meters. Using this system, it was confirmed that it could escape indoors.

    Improvements/Applications: The indoor disaster detection and escape route guidance system provides information on the existence of an indoor disaster. And the victim can identify safe escape routes.

     

     

  • References

    1. [1] Hong YS. Constructing Status of Overseas Disaster Networks & Trends in Disaster Communication Technology and Standards. TTA Journal; 2010. p. 44-50.

      [2] Kim SG, KIM TH, Tak SW. Performance Evaluation of RSSI-based Trilateraion Localization Methods. Journal of the Korea Institute of Information and Communication Engineering. 2011 Nov;15(11):2488-2492. Available from: http://www.dbpia.co.kr/Journal/ArticleDetail/NODE02245877

      [3] Rida ME, Liu F, Jadi Y, Algawhari AAA, Askourih A. Indoor location position based on Bluetooth signal strength. ICISCE:IEEE; 2015 April. p. 769-773. DOI:10.1109/ICISCE.2015.177

      [4] Chai S, An R, Du Z. An Indoor Positioning Algorithm Using Bluetooth Low Energy RSSI. International Conference on Advanced Material Science and Environmental Engineering. 2016.

      [5] Alliance Z. Zigbee-2006 specification. 2006. Available from: http://www.zigbee.org/

      [6] Alliance Z. IEEE 802.15.4. ZigBee standard. 2009.

      [7] Sichitiu ML, Ramadurai V. Localization of wireless sensor networks with a mobile beacon. MASS; 2004 July. p. 174-183

      [8] Thaljaoui A, Val T, Nasri N, Brulin D. BLE Localization using RSSI Measurements and iRingLA. ICIT:IEEE; 2015 march. p. 2178-2183. DOI:10.1109/ICIT.2015.7125418

      [9] Nasipuri A, Li K. A directionality based location discovery scheme for wireless sensor networks. ACM. 2012. p. 105-111. DOI:10.1145/570738.570754

      [10] Lorincz K, Welsh M. MoteTrack: A Robust, Decentralized Approach to RF-Based Location Tracking. International Symposium on Location-and Context-Awareness. 2005. p. 63-82

      [11] Nallapaneni Manoj Kumar, Sonali Goel, Pradeep Kumar Mallick, “Smart Cities in India: Features, Policies, Current Status, and Challenges†, IEEE International Conference on Technologies for Smart-City Energy Security and Power (ICSESP 2018), C. V. Raman College of Engineering, Bhubaneswar, March 28-30, 2018., Electronic ISBN: 978-1-5386-4581-9, DOI: 10.1109/ICSESP.2018.8376669.

  • Downloads

  • How to Cite

    Noh, D.-Y., Park, Y.-Y., Jung, K.-H., Lee, H.-W., & Kye, J.-E. (2018). Indoor Disaster Detection and Real-Time Escape Guidance System. International Journal of Engineering & Technology, 7(3.24), 370-374. https://doi.org/10.14419/ijet.v7i3.24.22688