Ontology-based big data analysis for orchid smart farming

Abstract

Background. Precision agriculture or smart farming is becoming more and more important in modern orchid farming in Thailand. Sensing and communication technologies have witnessed explosive growth in the recent past. These technologies are empowering information systems from many domains such as health care, environmental monitoring and farming, to collect and store large volume of data. Objectives. The research aims to develop an ontology for big data analysis for the smart farming in Rajamangala University of Technology Srivijaya (RUTS), Nakhon Si Thammarat campus. Methods. The ontology design and development process comprises: (1) Ontology design: the domain ontology provide vocabularies for concepts and relations within the orchid domain, and information ontology which specifies the record structure of databases; (2) Ontology development, which consists of five processes: (i) defining the scope, (ii) investigating the existing ontologies and plan to reuse, (iii) defining terms and its relations, (iv) create instances, and (v) implementation and evaluation. Results. The research outcome is the domain ontology and information ontology wherein 11 concepts of smart farming were identified and classified into classes and sub-classes. Contributions. The system is designed for assisting orchid farmers by giving recommended measures and expected results based on the knowledge extracted from best practices. © 2020, The authors Published by WKW School of Communication & Information & NTU Libraries, Nanyang Technological University volume 29, issue 2, pages 91-98 (2020)