空地协同的广域蔬菜种植传感数据采集研究  

Research on air-ground collaborative vegetable planting sensor data collection for wide-area

作　　者：李海燕 李博[2] 王美丽 张菁菁 Li Haiyan;Li Bo;Wang Meili;Zhang Jingjing(Dezhou Fruit and Vegetable Development Service Center,Dezhou 253000,Shandong,China;College of Infor-mation and Intelligent,Hunan Agricultural University,Changsha 410000,Hunan,China;JiuQuan Academy of Ag-ricultural Sciencese,Jiuquan 735000,Gansu,China;College of Computer Science,Central South University,Changsha 410000,Hunan,China)

机构地区：[1]德州市水产果蔬发展服务中心,山东德州253000 [2]湖南农业大学信息与智能科学技术学院,长沙410000 [3]酒泉市农业科学研究院,甘肃酒泉735000 [4]中南大学计算机学院,湖南长沙410000

出　　处：《中国农业信息》2024年第6期63-80,共18页China Agricultural Informatics

基　　金：山东省农业重大技术协同推广计划“‘吨半粮’小麦机艺融合绿色高产高效技术集成与协同推广”(SDNYXTTG-2023-32)。

摘　　要：【目的】针对大规模蔬菜种植区域传感器部署成本高昂、数据远距离传输困难等问题,设计高效的数据收集策略。【方法】文章结合蔬菜种植区域的分布特征,采用动态K均值聚类算法对区域进行分簇,通过贪心算法基于最近插入原则生成初始的卡车与无人机协同路径。之后利用基于进化的人工蜂群算法对路径进行优化,结合动态Metropolis准则、动态禁忌搜索和精英选择策略进一步提升解的质量。【结果】该方法显著减少了数据收集的总时间,同时大幅降低了空地采集系统的能耗。【结论】该文提出的方法为广域蔬菜种植区域的智能化数据收集提供了一种高效的解决方案,为实现精准农业的广泛应用提供了技术支撑。[Purpose]To promote the development of vegetable farming towards intelligence and precision,this paper proposes a truck-drone collaborative wide-area sensor data collection method.An efficient data collection strategy is designed to address the high cost of sensor deployment and the challenges of long-distance data transmission in large-scale vegetable farming areas.[Method]Based on the distribution characteristics of vegetable farming areas,a dynamic K-means clustering algorithm was used to partition the area into clusters.An initial truck-drone collaborative path was then generated using a greedy algorithm based on the nearest insertion principle.Subsequently,the path was optimized using an evolutionary artificial bee colony algorithm that incorporated the dynamic metropolis criterion,dynamic tabu search,and elite selection strategies to further improve solution quality.[Result]Experimental results showed that the proposed method effectively reduced the total data collection time and significantly lowered the energy consumption of the aerial-ground collection system.[Conclusion]The proposed method provides an efficient solution for intelligent data collection in wide-area vegetable farming and lays a solid foundation for the widespread application of precision agriculture.

关 键 词：精准农业 蔬菜种植 智慧农业 传感网络 无人机 

分 类 号：S126[农业科学—农业基础科学] TP393[自动化与计算机技术—计算机应用技术]