Abstract
Environmental sensing is the most crucial task that needs to be performed in order to analyze the situation of a region during a disaster. The devices deployed in such regions are responsible for sensing and communication effectively. During a disaster, the operation of these devices may be affected by the environmental conditions and their respective power constraints. Moreover, the mobility of these devices in the network leads to a challenging task to perform sensing and communication in such an environment. The disaster recovery may need different sensor data at various points of time. In such cases, the selectivity of data from different sensors and its dissemination in real time are the most important tasks. In this paper, the proposed algorithm is based on the situation-aware conditional sensing for disaster-prone areas using unmanned aerial vehicles. The technique presented in this paper focuses on the control of way points of the aerial vehicles based on the events detected in the Internet of Things environment.
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Cavallo, E., Noy, I., et al.: Natural disasters and the economy—a survey. Int. Rev. Environ. Resour. Econ. 5(1), 63–102 (2011)
Benfold, B., Reid, I.: Stable multi-target tracking in real-time surveillance video. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3457–3464 (2011)
Houston, J.B., Hawthorne, J., Perreault, M.F., Park, E.H., Goldstein Hode, M., Halliwell, M.R., Turner McGowen, S.E., Davis, R., Vaid, S., McElderry, J.A., et al.: Social media and disasters: a functional framework for social media use in disaster planning, response, and research. Disasters 39(1), 1–22 (2015)
Rose, A.: Economic resilience to natural and man-made disasters: multidisciplinary origins and contextual dimensions. Environ. Hazards 7(4), 383–398 (2007)
Zaveri, M.A., Kumar, J.S., Pandey, S.K., Choksi, M.: Collaborative Data Processing and Resource Optimization for Post Disaster Management and Surveillance using IoT. Technical Report from (MeitY), India (2016)
Bandyopadhyay, D., Sen, J.: Internet of Things: applications and challenges in technology and standardization. Wireless Pers. Commun. 58(1), 49–69 (2011)
Kumar, J.S., Zaveri, M.A.: Graph based clustering for two-tier architecture in Internet of Things. In: Proceedings of 9th IEEE International Conference on Internet of Things (iThings), pp. 229–233 (2016)
Pajares, G.: Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs). Photogram. Eng. Remote Sens. 81(4), 281–329 (2015)
Tuna, G., Nefzi, B., Conte, G.: Unmanned aerial vehicle-aided communications system for disaster recovery. J. Netw. Comput. Appl. 41, 27–36 (2014)
Reiter, G.: Wireless connectivity for the Internet of Things. Europe 433, 868 MHz (2014)
Mason, I.A., Nigam, V., Talcott, C., Brito, A.: A framework for analyzing adaptive autonomous aerial vehicles. In: Proceedings of the International Conference on Software Engineering and Formal Methods, pp. 406–422. Springer (2017)
Hasofer, A., Beck, V.R., Bennetts, I.: Risk Analysis in Building Fire Safety Engineering. Routledge (2006)
Plate, E.J.: Flood risk and flood management. J. Hydrol. 267(1–2), 2–11 (2002)
Yan, Y., Cheng, L., Wu, Z., Yam, L.: Development in vibration-based structural damage detection technique. Mech. Syst. Signal Process. 21(5), 2198–2211 (2007)
Davids, A.: Urban search and rescue robots: from tragedy to technology. IEEE Intell. Syst. 17(2), 81–83 (2002)
Hadi, G.S., Varianto, R., Trilaksono, B., Budiyono, A.: Autonomous UAV system development for payload dropping mission. J. Instrum. Autom. Syst. 1(2), 72–77 (2014)
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This work is supported by the Ministry of Electronics and Information Technology (MeitY), funded by Government of India (Grant no. 13(4)/2016-CC&BT).
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Sathish Kumar, J., Zaveri, M.A., Kumar, S., Choksi, M. (2019). Situation-Aware Conditional Sensing in Disaster-Prone Areas Using Unmanned Aerial Vehicles in IoT Environment. In: Jain, L., E. Balas, V., Johri, P. (eds) Data and Communication Networks. Advances in Intelligent Systems and Computing, vol 847. Springer, Singapore. https://doi.org/10.1007/978-981-13-2254-9_12
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DOI: https://doi.org/10.1007/978-981-13-2254-9_12
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