Automated zone-specific irrigation with wireless sensor/actuator network and adaptable decision support

WOS: 000338403000003Precision 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. (C) 2014 Elsevier B.V. All rights reserved.PLANTS project (IST FET Open) [IST-2001-38900]; PLANTS consortiumPart of the research described in this paper was conducted in the PLANTS project (IST FET Open IST-2001-38900); the authors wish to thank their fellow researchers in the PLANTS consortium for their input and support. We are grateful to professor Alan Cassells from the University College Cork for sharing his valuable insights regarding the plant science aspects of this research. The authors would also like to thank the anonymous reviewers for their helpful comments and constructive suggestions to improve the final version of the paper