Developing a Message Broadcasting System for Natural Disasters

Year 2021, Volume: 13 Issue: 1, 13 - 21, 18.01.2021

Veysel Harun Şahin İsmail Öztel

https://doi.org/10.29137/umagd.664730

Cited By: 1

Abstract

Natural disasters may cause fatal results on earth and often, it concludes with death and great destruction. One of the ways to cope with these effects is effective and continuous communication when the communication infrastructure destroyed with disasters. In this study, a message broadcasting system is proposed to enable the relief organizations to broadcast messages to the people in a disaster area even the communication infrastructures collapsed. The system uses smartphones for communication because of its widespread usage in the community. It consists of two mobile applications: master node and neighbor node. The master node is used to broadcast messages to disaster sufferers in the disaster area by relief organizations. The neighbor node receives the broadcasted message and also broadcasts the received message to other neighbor nodes. In the system, the communication between the smartphones were achieved by using Google Nearby Connections API. This API allows Android operating system smartphones to broadcast/discover each other and exchange messages regardless of network connectivity with the help of Bluetooth, Bluetooth Low Energy and Wi-Fi. In the context of this study, the proposed system was successfully developed and tested in different scenarios by using smartphones.

Keywords

Disaster, Emergency Communication, Mobile Application, Wireless Communication, Google Nearby Connections API

References

• Ahmed, A., Bakar, K. A., Channa, M. I., Khan, A. W., & Haseeb, K. (2017). Energy-aware and secure routing with trust for disaster response wireless sensor network. Peer-to-Peer Networking and Applications, 10(1), 216–237. https://doi.org/10.1007/s12083-015-0421-4
• Antonioli D., Tippenhauer N. O., Rasmussen K. B. (2019). Nearby Threats: Reversing, Analyzing, and Attacking Google’s ‘Nearby Connections’ on Android. Network and Distributed Systems Security (NDSS) Symposium 2019 (pp. 1-14). https://dx.doi.org/10.14722/ndss.2019.23367
• Arbia, D. Ben, Alam, M. M., Kadri, A., Hamida, E. Ben, & Attia, R. (2017). Enhanced IoT-based end-to-end emergency and disaster relief system. Journal of Sensor and Actuator Networks, 6(3), 1–18. https://doi.org/10.3390/jsan6030019
• Android. (n.d.). Best practices for unique identifiers. Retrieved August 7, 2019, from https://developer.android.com/training/articles/user-data-ids
• Aschenbruck, N., Gerharz, M., Frank, M., & Martini, P. (2006). Modelling Voice Communication in Disaster Area Scenarios. In Proceedings. 2006 31st IEEE Conference on Local Computer Networks (pp. 211–220). IEEE. https://doi.org/10.1109/LCN.2006.322102
• Chang-Richards, A., Seville, E., Wilkinson, S., & Walker, B. (2019). Effects of Disasters on Displaced Workers (pp. 185–195). https://doi.org/10.1007/978-3-319-92498-4_14
• CRED. (2019). Natural Disasters 2018. Brussels, Belgium.
• Eichinger T., Beierle F., Papke R., Rebscher L., Tran H. C., Trzeciak M. (2019). On gossip-based information dissemination in pervasive recommender systems. RecSys 2019 - 13th ACM Conference on Recommender Systems (pp. 442–446). https://doi.org/10.1145/3298689.3347067
• Google. (n.d.). Google Nearby Connections API. Retrieved August 7, 2019, from https://developers.google.com/nearby/connections/overview
• Guo, W., Huang, X., & Liu, Y. (2010). Dynamic relay deployment for disaster area wireless networks. Wireless Communications and Mobile Computing, (10), 1238–1252. https://doi.org/10.1002/wcm.679
• Khan, A., Munir, A., Kaleem, Z., Ullah, F., Bilal, M., et al. (2020). RDSP: Rapidly deployable wireless ad hoc system for post-disaster management. Sensors (Switzerland), 20(2), 1–21. https://doi.org/10.3390/s20020548
• Kim, S., Urata, Y., Koizumi, Y., & Hasegawa, T. (2015). Power-saving NDN-based message delivery based on collaborative communication in disasters. In The 21st IEEE International Workshop on Local and Metropolitan Area Networks (pp. 1–6). IEEE. https://doi.org/10.1109/LANMAN.2015.7114733
• Kousky, C. (2016). Impacts of Natural Disasters on Children. The Future of Children, 26(1), 73–92. https://doi.org/10.1061/(asce)0733-9402(2009)135:2(25)
• Krock, R. E. (2011). Lack of emergency recovery planning is a disaster waiting to happen. IEEE Communications Magazine, 49(1), 48–51. https://doi.org/10.1109/MCOM.2011.5681014
• Lesk, C., Rowhani, P., & Ramankutty, N. (2016). Influence of extreme weather disasters on global crop production. Nature, 529(7584), 84–87. https://doi.org/10.1038/nature16467
• Lu, X. (2018). Online communication behavior at the onset of a catastrophe: an exploratory study of the 2008 Wenchuan earthquake in China. Natural Hazards, 91:785–802. https://doi.org/10.1007/s11069-017-3155-1
• Mase, K., Azuma, N., & Okada, H. (2010). Development of an Emergency Communication System for Evacuees of Shelters. In 2010 IEEE Wireless Communication and Networking Conference (pp. 1–6). IEEE. https://doi.org/10.1109/WCNC.2010.5506628
• Meftah L., Rouvoy R., & Chrisment I. (2019). Testing Nearby Peer-to-Peer Mobile Apps at Large. In 2019 IEEE/ACM 6th International Conference on Mobile Software Engineering and Systems (MOBILESoft) (pp. 1–11). IEEE. https://doi.org/10.1109/MOBILESoft.2019.00009
• Menon, V. G., Pathrose, J. P., & Priya, J. (2016). Ensuring Reliable Communication in Disaster Recovery Operations with Reliable Routing Technique. Mobile Information Systems, 2016, 1–10. https://doi.org/10.1155/2016/9141329
• Menon, V. G. (2019). Optimized Opportunistic Routing in Highly Dynamic Ad hoc Networks. https://doi.org/10.20944/preprints201810.0478.v1
• Mezghani, F., & Mitton, N. (2017). Alternative opportunistic alert diffusion to support infrastructure failure during disasters. Sensors (Switzerland), 17(10). https://doi.org/10.3390/s17102370
• Ministry of Internal Affairs and Communications. (n.d.). Retrieved August 7, 2019, from http://www.soumu.go.jp/main_content/000117676.pdf
• Murugeswari, R., & Radhakrishnan, S. (2015). Reliable data delivery for emergency and disaster recovery in wireless mesh network. 2014 International Conference on Information Communication and Embedded Systems, ICICES 2014, (978), 1–6. https://doi.org/10.1109/ICICES.2014.7033950
• Noguchi, T., & Fujii, T. (2000). Minimizing the Effect of Natural Disasters. Japan Railway & Transport Review, 10(March), 52–59.
• Pogkas, N., Karastergios, G. E., Antonopoulos, C. P., Koubias, S., & Papadopoulos, G. (2007). Architecture Design and Implementation of an Ad-Hoc Network for Disaster Relief Operations. IEEE Transactions on Industrial Informatics, 3(1), 63–72. https://doi.org/10.1109/TII.2007.891307
• Schultz, C. H., Koenig, K. L., & Noji, E. K. (1996). A Medical Disaster Response to Reduce Immediate Mortality after an Earthquake. New England Journal of Medicine, 334(7), 438–444. https://doi.org/10.1056/NEJM199602153340706
• Shao, Z., Liu, Y., Wu, Y., & Shen, L. (2011). A Rapid and Reliable Disaster Emergency Mobile Communication System via Aerial Ad Hoc BS Networks. In 7th International Conference on Wireless Communications, Networking and Mobile Computing (pp. 1–4). IEEE. https://doi.org/10.1109/wicom.2011.6040479
• Sun, J., Zhu, X., Zhang, C., & Fang, Y. (2011). RescueMe: Location-based secure and dependable VANETs for disaster rescue. IEEE Journal on Selected Areas in Communications, 29(3), 659–669. https://doi.org/10.1109/JSAC.2011.110314
• Takasuka H., Hirai K., & Takami K., (2018). Development of a social DTN for message communication between SNS group members. Future Internet, 10(4), 1–20. https://doi.org/10.3390/fi10040032
• Townsend, A. M., & Moss, M. L. (2005). Telecommunications Infrastructure In Disasters: Preparing Cities for Crisis Communications. New York, NY, USA. Retrieved from https://www.nyu.edu/ccpr/pubs/NYU-DisasterCommunications1-Final.pdf
• Tuna, G., Mumcu, T. V., & Gulez, K. (2012). Design strategies of unmanned aerial vehicle-aided communication for disaster recovery. High Capacity Optical Networks and Emerging/Enabling Technologies. IEEE. https://doi.org/10.1109/HONET.2012.6421446
• Uchida, N., Takahata, K., & Shibata, Y. (2011). Cognitive Wireless Network for Large Scale Disaster. In 2011 Third International Conference on Intelligent Networking and Collaborative Systems (pp. 362–366). IEEE. https://doi.org/10.1109/INCoS.2011.64