University of Bahrain
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Plant Health Detection Enabled CNN Scheme in IoT Network

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dc.contributor.author Panhwar, Ali Orangzeb
dc.contributor.author Sathio, Anwar Ali
dc.contributor.author Shaikh, Mujeeb ur Rehman
dc.contributor.author Lakhan, Abdullah
dc.contributor.author Umer, Muhammad
dc.contributor.author Mithiani, Rabia Mushtaque
dc.contributor.author Khan, Sanwali
dc.date.accessioned 2022-03-09T12:15:43Z
dc.date.available 2022-03-09T12:15:43Z
dc.date.issued 2022-03-09
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/4604
dc.description.abstract Green Environment is a key for Healthy Environment, to keep environment green every country doing a lot to preserve their Healthy growth in the agriculture. The detection of diseases in plants is very hard job and will have a significant impact of environmental development growth as well as production. This study aimed to detect unhealthy plants through infected leaves using CNN enabled method helped to mitigate the worst situation for the less developed countries. This research study had modelled the IoT network-based Plant Health Detection System, in which we explored the different invisible patterns of plant leaves which can’t be detected easily in the plants. In this research article, we have investigated and developed a IoT-network system with a CNN model successfully that can detect the invisible micro things in the plants by getting 93.70 percent of accuracy in the study. In this research study, we used IoT-Network system by applying the CNN technique to train the model for detection of diseases in leaves. This model scheme provided the best performance detection with an accuracy of 93.70 percent, demonstrating the performance of the proposed CNN scheme after implementation. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject CNN en_US
dc.subject IoT en_US
dc.subject Leaves Disease en_US
dc.subject Detection en_US
dc.subject Leaves Pattern en_US
dc.subject Plant Health en_US
dc.title Plant Health Detection Enabled CNN Scheme in IoT Network en_US
dc.identifier.doi https://dx.doi.org/10.12785/ijcds/120127
dc.volume 11 en_US
dc.issue 1 en_US
dc.pagestart 344 en_US
dc.pageend 335 en_US
dc.contributor.authoraffiliation Lab of AI and Information Security, Department of Computer Science and Information Technology,Benazir Bhutto Shaheed University Lyari, Karachi , Sindh, Pakistan en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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