An Ontology-based Automation System: A Case Study of Citrus Fertilization

Tracking #: 2141-3354

This paper is currently under review
Authors: 
Jianwei Liao
Yi Wang
Jinyuan Wang
Xiao Wen

Responsible editor: 
Guest Editors Semantic E-Science 2018

Submission type: 
Full Paper
Abstract: 
This paper conducts a motivation case study about automatic fertilization for citrus planting, to illustrate the feasibility and applicability of ontology-based automation systems in precision agriculture. Specifically, we first build a citrus fertilization ontology on the basis of the citrus production knowledge in the forms of texts, tables and pictures from technical reports and books. Next, we utilize semantic techniques, including RDF-based (Resource Description Framework) representation, semantic reasoning (The Ontology Web Language, OWL), and probability modeling, to manage the fertilization ontology, for providing integrated and accurate fertilization recommendations. Then, we integrate the constructed ontology with an automatic fertilization machine, to create our target semantic-based automation system. At last, we run experiments with our proposed system, and compare its outputs with the reference values advised by the agri-professionals of citrus planting. The results show that our system can offer better fertilization recommendation services, to trigger automatic production.
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