Situation-Aware Conditional Sensing in Disaster-Prone Areas Using Unmanned Aerial Vehicles in IoT Environment
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.
KeywordsDisaster management Unmanned aerial vehicles Internet of things
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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