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Automated zone-specific irrigation with wireless sensor/actuator network

机译:通过无线传感器/执行器网络自动进行特定区域灌溉

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摘要

Precision irrigation based on the "speaking plant" approach can save water and maximize crop yield, but implementing irrigation control can be challenging in system integration and decision making. In this paper we describe the design of an adaptable decision support system and its integration with a wireless sensor/actuator network (WSAN) to implement autonomous closed-loop zone-specific irrigation. Using an ontology for defining the application logic emphasizes system flexibility and adaptability and supports the application of automatic inferential and validation mechanisms. Furthermore, a machine learning process has been applied for inducing new rules by analyzing logged datasets for extracting new knowledge and extending the system ontology in order to cope, for example, with a sensor type failure or to improve the accuracy of a plant state diagnosis. A deployment of the system is presented for zone specific irrigation control in a greenhouse setting. Evaluation of the developed system was performed in terms of derivation of new rules by the machine learning process, WSN performance and mote lifetime. The effectiveness of the developed system was validated by comparing its agronomic performance to traditional agricultural practices.
机译:基于“说植物”方法的精确灌溉可以节水并最大程度提高农作物的产量,但是实施灌溉控制可能对系统集成和决策提出挑战。在本文中,我们描述了适应性决策支持系统的设计及其与无线传感器/执行器网络(WSAN)的集成,以实现特定于区域的自主闭环灌溉。使用本体定义应用程序逻辑强调了系统的灵活性和适应性,并支持自动推理和验证机制的应用。此外,已经通过分析记录的数据集以提取新知识并扩展系统本体来应用机器学习过程来诱导新规则,以应对例如传感器类型故障或提高工厂状态诊断的准确性。提出了该系统的部署,用于温室环境中特定区域的灌溉控制。在通过机器学习过程,WSN性能和节点寿命推导新规则方面,对开发的系统进行了评估。通过将其农艺性能与传统农业实践进行比较,验证了开发系统的有效性。

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