Abstract
An important part of environmental monitoring is the collection of meteorological data. In this paper, we develop an integrated data acquisition and transmission platform utilizing unmanned aerial vehicles (UAVs) with an intelligent path planning algorithm to achieve efficient and accurate meteorological data collection in real-time. We adopt the improved traveling salesman problem model to represent the path planning problem. Based on the model, we propose an improved simulated annealing genetic algorithm (ISAGA) to solve the path planning problem. Our proposed ISAGA is able to overcome the deficiencies of the traditional genetic algorithm and simulated annealing algorithm. In addition, we design and implement a mobile application integrated with the path planning algorithm to control UAVs and conduct data exchange to the cloud. Our evaluation results demonstrate that data can be collected and transmitted more efficiently via selecting better paths.
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Acknowledgment
The work of Zhangjie Fu is partially supported by the National Natural Science Foundation of China (NSFC) under grant U1836110, U1836208, U1536206, 61602253, 61672294; the National Key R&D Program of China under grant 2018YFB1003205; the Jiangsu Basic Research Programs-Natural Science Foundation under grant BK20181407; the Priority Academic Program Development of Jiangsu Higher Education Institutions fund; the Major Program of NSFC (17ZDA092), Qing Lan Project; the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology fund, China; the Opening Project of Guangdong Provincial Key Laboratory of Data Security and Privacy Protection (No. 2017B03031004). The work of Liran Ma is partially supported by the US National Science Foundation (No. OAC1829553).
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Xu, L., Fu, Z., Ma, L. (2019). An Integrated UAV Platform for Real-Time and Efficient Environmental Monitoring. In: Biagioni, E., Zheng, Y., Cheng, S. (eds) Wireless Algorithms, Systems, and Applications. WASA 2019. Lecture Notes in Computer Science(), vol 11604. Springer, Cham. https://doi.org/10.1007/978-3-030-23597-0_32
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DOI: https://doi.org/10.1007/978-3-030-23597-0_32
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