Plant Disease Detection and Solution for Rural Farmers Using Computer Vision, Cloud Computing and Android Platform

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creativework.keywordsElectrical engineering, Cloude computing, Disease ditection
dc.contributor.advisorMd. Shahriar Karim
dc.contributor.authorMohammad Rashedul Alam
dc.contributor.authorSakib Mukter
dc.contributor.authorAminul Islam
dc.contributor.id1511384042
dc.contributor.id1520268042
dc.contributor.id1520523042
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2024-05-29
dc.date.accessioned2024-05-29T05:41:05Z
dc.date.available2024-05-29T05:41:05Z
dc.date.issued2019
dc.description.abstractBangladesh is a densely populated country with considerably low per capita arable land, which makes a daunting task to grow sufficient food grains for about its 160 million people. Diseases prevalence and the lack of close monitoring often results in crop loss as high as 30% in some cases. For instance, rice production reduces by about 10% because of diseases, whereas potato and tomato production decreases by 37% and 43% respectively because of leaf infection. Early and accurate detection of these diseases can prevent a large-scale yield loss. However, detection of these diseases is hard for farmers without the direct help of skilled people. To provide the farmers with the initial information, we develop a voice assisted mobile app that can predict a possible set of diseases from the images of leaf-infection. The App is optimized against low-resolution images and includes voice assistance at its every step to ensure usability for the farmers, who are generally are uncomfortable with digital platforms. Also, the App also suggests possible remedies for the affected crops, and the information of sellers and distributors of pesticides, fertilizers, and other relevant commodities. Together, this App attempts to increase crops yield and is expected to act as the bridge between the sellers, distributors and the farmers living in the farthest corner of our country.
dc.description.degreeUndergraduate
dc.identifier.cd600000070
dc.identifier.print-thesisTo be assigned
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/839
dc.language.isoen_US
dc.publisherNorth South University
dc.rights© NSU Library
dc.titlePlant Disease Detection and Solution for Rural Farmers Using Computer Vision, Cloud Computing and Android Platform
dc.typeThesis
oaire.citation.endPage72
oaire.citation.startPage1
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