Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/11524
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dc.contributor.authorTilva, Vidita R.
dc.date.accessioned2023-04-20T10:57:50Z-
dc.date.available2023-04-20T10:57:50Z-
dc.date.issued2014-06-01
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/11524-
dc.description.abstractIntegrated Pest Management (IPM) is a comprehensive approach that integrates a variety of practices to minimize the loss of farm productions due to pests and pathogens with optimum use of pesticides. Early detection of pest and its control is one of the aspects of IPM. Weather based forecasting is well accepted method for this. Various meteorological data like- temperature, humidity, leaf wetness duration (LWD) plays the vital roles in the growth of microorganism responsible for disease. Effective forecasting of sthe farmers to take timely actions to restrain the diseases. This can also rationalize the use of pesticides, which are one of the causes behind land pollution. Weather based forecasting system can be considered as a part of the Agricultural Decision Support System (ADSS) which is wledge Based System (KBS). This Report suggest fuzzy logic based structure for the plant disease forecasting system. It has been demonstrated that the proposed method can be implemented with minimum weather data like- temperature and humidity. Weather based plant disease forecasting system is deployed in Open source platform like JAVA so, farmers can get the maximum advantage of this system.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries11MICC51;
dc.subjectIC 2012en_US
dc.subjectProject Report 2012en_US
dc.subjectIC Project Reporten_US
dc.subjectProject Reporten_US
dc.subject12MICen_US
dc.subject12MICCen_US
dc.subject11MICC51en_US
dc.subjectControl & Automationen_US
dc.subjectControl & Automation 2012en_US
dc.subjectIC (Control & Automation)en_US
dc.titleeather based Plant Diseases Forecasting Using Fuzzy Logicen_US
dc.typeDissertationen_US
Appears in Collections:Dissertations, E&I

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