作物自主灌溉的多智能体系统框架

Alfonso González-Briones, José A. Castellanos-Garzón, Yeray Mezquita-Martín, Javier Prieto, J. Corchado
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引用次数: 8

摘要

本文介绍了一种创新的多智能体系统(MAS)的设计和开发,该系统由不同的子系统组成,这些子系统按其任务的相似性分组。所提出的MAS将管理从无线传感器网络捕获的信息,以便在农村环境中在执行器网络上进行知识发现和决策。拟议的MAS建立在云计算范式的基础上,以在小型和大型项目的管理中提供更大的灵活性和可扩展性。在农村地区使用这些“智能”技术可以提高农业生产系统的效率和有效性,分析传感器收集的数据,提取模式以预测影响作物的事件,并通过自动执行器预测这些事件并给出局部响应。为了优化玉米作物的灌溉,所提出的建筑已经在农业环境中进行了测试。通过无线传感器网络(WSN),可以获取作物地形和气候条件的信息,提取有关种植玉米需求的信息,并根据这些需求做出有效的灌溉决策,与传统的汽车灌溉相比,减少了17.16%的用水量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi-agent system framework for autonomous crop irrigation
This article presents the design and development of an innovative multi-agent system (MAS) composed of various subsystems of agents grouped by similarity in their tasks. The proposed MAS will manage the information captured from wireless sensor networks for knowledge discovery and decision making in rural environments on actuator networks. The proposed MAS has been built on the Cloud Computing paradigm to provide greater flexibility and scalability in the management of both small and large projects. The use of these “intelligent” technologies in rural areas can improve the efficiency and effectiveness of agricultural production systems, analyzing the data collected by sensors, extracting patterns to predict events affecting the crop and anticipate such events giving localized responses with automated actuators. The proposed architecture has been tested in an agricultural environment in order to optimize irrigation in a corn crop. Thanks to the wireless sensor network (WSN), information has been obtained about the terrain of the crop and its climatic conditions, extracting information about the needs of cultivated corn and taking efficient irrigation decisions based on those needs, reducing water consumption by 17.16% compared to traditional automotive irrigation.
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