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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kirkpatrick, S., Gelatt, D., Vecchi, M.: Optimization by simulated annealing. Science 220(4598), 671–680 (1983)
Tsai, C.-F., Tsai, C.-W., Yang, T.: A modified multiple-searching method to genetic algorithms for solving traveling salesman problem. In: IEEE International Conference on Systems, Man and Cybernetics, vol. 3, pp. 6-pp. IEEE (2002)
De, J., Kenneth, A.: An Analysis of the Behavior of a Class of Genetic Adaptive Systems (1975)
Rudolph, G.: Convergence analysis of canonical genetic algorithms. IEEE Trans. Neural Netw. 5(1), 96–101 (1994)
Wang, Y.: Development and current situation of environmental monitoring system. Technol. Wind 30(26), 107 (2017)
Zhong, L., Zheng, J., Lei, G., Chen, J., Che, W.: Development status and trend analysis of air quality monitoring network. Environ. Monit. China 33(02), 113–118 (2007)
Zhang, Q., Chen, C., Wu, D.: Study on the application of remote sensing technology in environmental monitoring. J. Green Sci. Technol. 6(03), 235–236 (2015)
Huang, Y., Jiangdong, Zhuang, D., Fu, J.: Remote sensing estimation of chlorophyll concentration in lake townsend. J. Nat. Disasters 21(02), 215–222 (2012)
Zhu, J., Xu, G., Liu, J.: Application of UAV remote sensing system in the field of environmental protection. Environ. Prot. Recycl. Econ. 31(09), 45–48 (2011)
Yang, H., Huang, Y.: Remote sensing monitoring of chemical polluted gases by UAV. J. Geo-Inf. Sci. 17(10), 1269–1274 (2015)
Gatsonis, N.A., Demetriou, M.A., Egorova, T.: Real-time prediction of gas contaminant concentration from a ground intruder using a UAV. In: 2015 IEEE International Symposium on Technologies for Homeland Security (HST), pp. 1–6. IEEE (2015)
Cai, Z., Zheng, X.: A private and efficient mechanism for data uploading in smart cyber-physical systems. IEEE Trans. Netw. Sci. Eng. (2018)
Li, J., Cheng, S., Cai, Z., Yu, J., Wang, C., Li, Y.: Approximate holistic aggregation in wireless sensor networks. ACM Trans. Sen. Netw. 13(2), 11:1–11:24 (2017)
Cheng, S., Cai, Z., Li, J., Gao, H.: Extracting kernel dataset from big sensory data in wireless sensor networks. IEEE Trans. Knowl. Data Eng. 29(4), 813–827 (2017)
Danilov, A., Smirnov, U.D., Pashkevich, M.: The system of the ecological monitoring of environment which is based on the usage of UAV. Russ. J. Ecol. 46(1), 14–19 (2015)
Dantzig, G., Johnson, S.: Solution of a large-scale traveling-salesman problem. Oper. Res. 2(4), 393–410 (2010)
Tsai, C.-F., Tsai, C.-W., Tseng, C.-C.: A new hybrid heuristic approach for solving large traveling salesman problem. Inf. Sci. 166(1–4), 67–81 (2004)
Cochrane, E., Beasley, J.: The co-adaptive neural network approach to the Euclidean travelling salesman problem. Neural Netw. 16(10), 1499–1525 (2003)
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. IEEE (1955)
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).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-23597-0_32
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23596-3
Online ISBN: 978-3-030-23597-0
eBook Packages: Computer ScienceComputer Science (R0)