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A Formal Model for Managing Multiple Observation Data in Agriculture

Watanee Jearanaiwongkul, Frederic Andres and Chutiporn Anutariya
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Watanee Jearanaiwongkul: Asian Institute of Technology, Pathum Thani, Thailand
Frederic Andres: National Institute of Informatics, Tokyo, Japan
Chutiporn Anutariya: Asian Institute of Technology, Pathum Thani, Thailand

International Journal of Intelligent Information Technologies (IJIIT), 2019, vol. 15, issue 3, 79-100

Abstract: Nowadays, farmers can search for treatments for their plants using search engines and applications. Most existing works are developed in the form of rule-based question answering platforms. However, an observation could be incorrectly given by the farmer. This work recommends that diseases and treatments must be considered from a set of related observations. Thus, we develop a theoretical framework for systems to manage a farmer's observation data. We investigate and formalize desirable characteristics of such systems. The observation data is attached with a geolocation in which related contextual data is found. The framework is formalized based on algebra, in which required types and functions are identified. Its key characteristics are described by: (1) the defined type called warncons for representing observation data; (2) the similarity function for warncons; and (3) the warncons composition function for composing similar warncons. Finally, we show that the framework helps observation data to become richer and improve advice-finding.

Date: 2019
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