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However, sensor nodes have limited storage capacity and battery power. The WSNs are faced with the challenge of handling larger data volumes while minimizing energy consumption for transmission. To address this issue, this paper employs data compression technology to eliminate redundant information in the environmental data, thereby reducing energy consumption of sensor nodes. Additionally, an unmanned aerial vehicle (UAV)-assisted compressed data acquisition algorithm is put forward. In this algorithm, compressive sensing (CS) is introduced to decrease the amount of data in the network and the UAV serves as a mobile aerial base station for efficient data gathering. Based on CS theory, the UAV selectively collects measurements from a subset of sensor nodes along a route planned using the optimized greedy algorithm with variation and insertion strategies. Once the UAV returns, the sink node reconstructs sensory data from these measurements using the reconstruction algorithms. Extensive experiments are conducted to verify the performance of this algorithm. Experimental results show that the proposed algorithm has lower energy consumption compared to other approaches. Furthermore, we employ different data reconstruction algorithms to recover data and discover that the data can be better reconstructed in a shorter time.<\/jats:p>","DOI":"10.3390\/s23208546","type":"journal-article","created":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T10:36:56Z","timestamp":1697625416000},"page":"8546","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Unmanned Aerial Vehicle-Based Compressed Data Acquisition for Environmental Monitoring in WSNs"],"prefix":"10.3390","volume":"23","author":[{"given":"Cuicui","family":"Lv","sequence":"first","affiliation":[{"name":"School of Computer and Control Engineering, Yantai University, Yantai 264005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linchuang","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer and Control Engineering, Yantai University, Yantai 264005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinxin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Central Research Institute, Yantai Jereh Oilfield Services Group Co., Ltd., Yantai 264003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangming","family":"Li","sequence":"additional","affiliation":[{"name":"School of Environment and Materials Engineering, Yantai University, Yantai 264005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peijin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Control Engineering, Yantai University, Yantai 264005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenbin","family":"Du","sequence":"additional","affiliation":[{"name":"School of Computer and Control Engineering, Yantai University, Yantai 264005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","article-title":"Compressed sensing","volume":"52","author":"Donoho","year":"2006","journal-title":"IEEE Trans. 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