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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