A Systematic Review of Knowledge Representation Techniques in Smart Agriculture (Urban)

Bikram Pratim Bhuyan (), Ravi Tomar and Amar Ramdane Cherif
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Bikram Pratim Bhuyan: School of Computer Science, University of Petroleum and Energy Studies, Dehradun 248006, India
Ravi Tomar: Persistent Systems, Pune 411016, India
Amar Ramdane Cherif: LISV Laboratory, University of Paris Saclay, 10-12 Avenue of Europe, 78140 Velizy, France

Sustainability, 2022, vol. 14, issue 22, 1-36

Abstract: Urban agriculture is the practice of growing food inside the city limits. Due to the exponential amount of data generated by information and technology-based farm management systems, we need proper methods to represent the data. The branch of artificial intelligence known as “knowledge representation and reasoning” is devoted to the representation of information about the environment in a way where a computer system can utilise it to accomplish difficult problems. This research is an extensive survey of the knowledge representation techniques used in smart agriculture, and specifically in the urban agricultural domain. Relevant articles on the knowledge base are extracted from the retrieved set to study the fulfillment of the criteria of the system. Various interesting findings were observed after the review. Spatial–temporal characteristics were rarely approached. A generalised representation technique to include all domains in agriculture is another issue. Finally, proper validation technique is found to be missing in such an ontology.

Keywords: knowledge representation; sustainable agriculture; smart urban agriculture; ontology; Semantic Web; artificial intelligence in agriculture (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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