Design of an Indoor Disaster Routing Protocol

  • Authors

    • Kang-Hee Jung
    • Hye Sun Ahn
    • Manh-Luong Tien
    • Yoon-Young Park
    • Joong Eup Kye
    https://doi.org/10.14419/ijet.v7i3.24.22685
  • Indoor Disaster, IoT, Routing Protocol, Indoor Geospatial Information, SLAM, RNN
  • Background/Objectives: We suffer a lot of casualties every year from some disaster situations, such as fire or gas leaks that occur indoors. The research is needed to minimize the harm of disaster.

    Methods/Statistical analysis: When the disaster happens, the evacuation route changes every minute due to obstacles or dangerous situations. To solve this problem, we must collect map data and sensor information periodically. Then this information is used to calculate the evacuation route. In addition, the sensor data of the node transfer to a server in order to utilize the prediction of evacuation path using the RNN.

    Findings: In many developed countries, a lot of research are launched to prevent disasters rather than response when the disaster occurs. However, guiding evacuation routes in real situations is an aspect of the disaster response, which requires disaster sensor data. In addition, in a disaster situation, some areas cannot go through by people due to fire or gas leakage. In order to efficiently guide the evacuation route, techniques for producing a map in real time and sensor (actual and predicted) data are required. At this time, the map data is converted into the topology map by using the image obtained through the SLAM technology, and the sensor data predicts the next value based on the previous data through the RNN (using the sensor data to predict). Consequently, the proposed Routing Protocol in Indoor Disaster (RPID) guides the evacuator to a path with a short cumulative damage amount.

    Improvements/Applications: Depending on the routing protocol used in the simulator or the technique of locating the user's location information, we can develop an evacuation system which can help victim find a safe way to escape as fast as possible from the dangerous situation.

     

     

  • References

    1. [1] Sim KS, Kim HS, Yu SG, Kim SM. Estimation of the Formaldehyde Concentration of Subterranean Shopping Centers according to their Spatial Configuration and Renovation, Journal of the Korean Furniture Society. Journal of the Korean Furniture Society. 2014;25(3):182-7.

      [2] H YS. Construction status of overseas disaster networks and trends in disaster communication technology and standards. Telecommunications Technology Association Journal. 2010;131:40–50.

      [3] Korean Institute of Electromagnetic Engineering and Science Report. Applicability Research and Service on Commercial Network about Constructor of Disaster Public Safety Communication to Necessary Correspond to Disaster; c2012. Chapter 3, Overseas case analysis; p. 10-16

      [4] Kim JH, L TH, Cho SH, Cho JD. Proposal Fire Evacuation Routes System using IoT. Extended Abstracts of HCI Korea 2016. 2016 Jan:413-4.

      [5] Yoon MH, Kwon YJ. A study on the reaction mechanism on the harmful gases related to the human physiology caused by fire and panic phenomenon. Korean Institute of Fire Science & Engineering. 2008 Apr: 337-40.

      [6] Park MS. Disaster Management of Building and Distributed Simulation Platform. Review of Architecture and Building Science. 2013;57(3): 32-6.

      [7] J CM. Developing a dynamic evacuation guiding system based on indoor sensor for real-time evacuation guidance. University of Seoul Industry-Academia Collaboration Foundation 2016 May; p. 13-8.

      [8] Li KJ. Geocoding Scheme for Multimedia in Indoor Space Based on IndoorGML. Korea Spatial Information Society. 2013 Aug; 21(4): 35-45. http://dx.doi.org/10.12672/ksis.2013.21.4.035.

      [9] Fabian B, Marius F, Marcin D, Thomas S, Roland S. Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps. 2018 Mar: 1-8.

      [10] Richard B, Florian J, Wenzhe L, Joshua H, Martin H. Room Segmentation: Survey, Implementation, and Analysis. IEEE International Conference on Robotics and Automation. 2016 Mar: 1019-26.

      [11] Winter T, Thubert P, RPL: IPv6 Routing Protocol for Low power and Lossy Networks. IETF RFC 6550. 2012.

      [12] Dhafer BA, Muhammad MA, Rabah A, Elyes BH. A Novel Multi-Hop Body-to-Body Routing Protocol for Disaster and Emergency Networks. WinCOM. 2017 Oct: 1-7.

      [13] Carli M, Panzieri S, Pascucci F. A Joint Routing and Localization Algorithm for Emergency Scenarios. 2014 Feb; 13(1): 19-33. https://doi.org/10.1016/j.adhoc.2012.09.001.

      [14] Jo HY, Kim JH, Kim KM, Chang JH, Eom JH, Zhang BT. Large-Scale Text Classification with Recurrent Neural Networks. Korea Computer Congress. 2016: 968-70.

      [15] Indoor air quality [Internet]. WIKIPEDIA. 2018 [updated 2018 Sep 12; cited 2018 Sep 12]. Available from: https://en.wikipedia.org/wiki/Indoor_air_quality

      [16] Battalion Chief Ed Hartin, MS, EFO, MLFireE, CFO. Fire Development and Fire Behavior Indicators. [Image on internet]. [cited 2018 Sep 10]. Available from: http://cfbt-us.com/pdfs/FBIandFireDevelopment.pdf

      [17] Vytenis B. Temperatures in flames and fires. Fire Science and Technology. [Internet]. 1997 [updated 2006 Feb 25; cited 2018 Sep 13]. Available from: https://www.doctorfire.com/flametmp.html

      [18] John E, Hanna KU. Acclimatization to Heat in Humans. NASA Technical Memorandum 101011. 1989 Apr: 1-43.

      [19] phiko.kr: The effect of indoor carbon dioxide concentration on human body [Internet]. Korea: Passive House Institute Korea. 2013 [cited 2018 Sep 10]. Available from: http://www.phiko.kr/bbs/board.php?bo_table=z3_01&wr_id=452

  • Downloads

  • How to Cite

    Jung, K.-H., Sun Ahn, H., Tien, M.-L., Park, Y.-Y., & Eup Kye, J. (2018). Design of an Indoor Disaster Routing Protocol. International Journal of Engineering & Technology, 7(3.24), 356-360. https://doi.org/10.14419/ijet.v7i3.24.22685