Ontology Based Expert System for Pests and Disease Management of Cotton Crop in India

Ontology Based Expert System for Pests and Disease Management of Cotton Crop in India

Mahesh D. Titiya, Vipul A. Shah
Copyright: © 2018 |Pages: 18
DOI: 10.4018/IJWP.2018070103
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In the agricultural domain, the main challenge is to present the new information and research to the farmers so that they can leverage the power of technologies to improve their agricultural practices and thereby the production. Huge amounts of agriculture-related data like weather data, soil health records, disease and pest are collected from different sources like web services, remote satellites, and a network of sensors. The authors' ontology-based agro advisory system will help to bridge the gap between farmers and the agriculture domain experts. It has three main components: Cotton Ontology, Web services and Mobile Application Development. Protégé tool is used to develop ontology. The RESTful web services are programmed in Java using the JAX-RS/Jersey API and Eclipse IDE. RESTful web services are all developed and deployed on a cloud-based application server provided by Heroku. The farmers can access an application by android mobile. The Android user interface is created using Java, Android SDK-v1.4 and Eclipse IDE.
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During literature survey, we found existing Agro Advisory systems like eSagu (P. Krishna Reddy, 2007), Agrisnet (Agrisnet, 2014), Kissan Kerala (KissanKerela, 2014), aAQUA (RamamrithamKrithi, 2004), mKrishi (ArunPande, 2009).

eSagu is a web-based recommended system for an agricultural domain. It uses web technology to resolve the problems of agriculture. The eSagu project initiated in Telangana city of Andhra Pradesh state. The meaning of eSagu is cultivation in the Telugu language. It exploits the inventions made in computing era to construct an agricultural information broadcasting system to spread the expert’s knowledge or expertise to the farmers which lead to increase in crop production. It is developed by Media Labs Asia. Its advice to the farmers for improving farm productivity. The farmer can send the status of their crop by sending text or photographs. Based on the status of crop agricultural experts give advice farmers.

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