Abstract
In recent years, information technology has played a decisive role in farm management through the exploitation of smart sensors and IoT devices. The introduction of IoT has improved the entire agricultural process chain, from Smart Irrigation to Smart Seeding. Another interesting aspect regards the application of semantic and artificial intelligence techniques to these sectors. This work moves in this direction, providing a methodology for the implementation of an expert system helping the smart management of irrigation systems using an approach based on ontologies, BPMN semantic annotation and logical inference techniques. Through the Irrig ontology, proposed by the INRAE research centre as the knowledge base, the expert system aims at providing decision support for the automatic activation of actuators of smart irrigation systems, and verifying the compliance of farm business processes with the related regulations, using an approach based on the Business Process Patterns discovery in semantically annotated BPMNs.
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Technologies et Systèmes dinformation pour les agrosystèmes Clermont-Ferrand.
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National Research Institute for Agriculture, Food and the Environment.
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The work described in this paper has been supported by the Project VALERE SSCeGov - Semantic, Secure and Law Compliant e-Government Processes.
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Di Martino, B., Cante, L.C., Esposito, A., Graziano, M. (2023). Towards a Methodology for the Semantic Representation of Iot Sensors and BPMNs to Discover Business Process Patterns: A Smart Irrigation Case Study. In: Barolli, L. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2022. Lecture Notes in Networks and Systems, vol 570. Springer, Cham. https://doi.org/10.1007/978-3-031-20029-8_24
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