基于无人飞行器的果园监测和人工神经网络的图像处理:系统性审查
Dan Popescu1, Loretta Ichim1, Florin Stoican1
1Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, Bucharest, Romania.
Frontiers in plant science
|December 13, 2023
概括
本综述探讨了利用人工智能和无人机 (UAV) 进行果园监测的进展. 它分析神经网络和无人机应用程序,以改善水果生产和树木健康管理.
科学领域:
- 农业技术 农业技术
- 计算机科学 计算机科学
- 遥感 遥感 遥感 遥感
背景情况:
- 果园监测对于提高水果产量至关重要.
- 技术进步和设备成本的降低推动了使用无人机和人工智能 (AI) 进行果园监测的进展.
- 最近的发展重点是将AI算法与无人机集成,以在果园中进行复杂的图像采集和处理.
研究的目的:
- 审查当前果园监测的研究趋势,重点关注神经网络,无人机及其应用.
- 分析神经网络 (AI) 和无人机在2017年至2022年间果园监测和生产评估中的整合.
- 为研究人员和最终用户提供关于在果园管理中实施新概念的见解和建议.
主要方法:
- 系统分析科学论文,结合与果园监测,神经网络和无人机相关的关键词.
- 专注于2017年至2022年间出版的文学作品.
- 详细检查基于无人机的果园应用程序的神经网络系统,数据库,软件和性能指标.
主要成果:
- 确定了关键应用,包括果园/树/冠状的识别和细分.
- 突出了树木疾病,害虫和有害昆虫的检测.
- 强调使用人工智能和无人机评估水果生产和树木发展条件.
- 在果园环境中分析无人机轨迹和飞行特征.
结论:
- 神经网络和无人机的集成代表了果园监测的重大进步.
- 这些技术为精确的水果生产评估和早期发现疾病和害虫等问题提供了强大的工具.
- 建议进行进一步的研究和实施,以利用这些进展来实现可持续和高效的水果种植.
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