GreenGuard: : An Android-Based Application for Early Disease Detection of Indoor Plant
Numerous individuals like the hobby of taking care of indoor plants, which provides both aesthetic and health benefits. However, they may be susceptible to a variety of disorders, as is the case with other plants. Manually identifying plant diseases is a time-consuming, error-prone, and unreliable p...
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| Những tác giả chính: | , |
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| Định dạng: | Online |
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
Jahangirnagar University
2024
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| Những chủ đề: | |
| Truy cập trực tuyến: | http://journals.juniv.edu/index.php/jit/article/view/156 |
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| _version_ | 1873958280547532800 |
|---|---|
| author | Rahman, Md. Mahmudur Tumpa, Samira Akter |
| author_facet | Rahman, Md. Mahmudur Tumpa, Samira Akter |
| author_sort | Rahman, Md. Mahmudur |
| collection | OJS |
| description | Numerous individuals like the hobby of taking care of indoor plants, which provides both aesthetic and health benefits. However, they may be susceptible to a variety of disorders, as is the case with other plants. Manually identifying plant diseases is a time-consuming, error-prone, and unreliable process that impedes the ability to effectively identify and prevent them. The challenges can be surmounted by the early and precise detection of interior plant diseases by implementing new technologies such as Deep Learning and Machine Learning . In this research, we introduce 'GreenGuard,' a revolutionary solution for indoor plant devotees. This study employs critical deep-learning models to identify plant diseases, including ResNet50, VGG16, EfficientNetB0, EfficientNetB5, and EfficientNetB7. Models such as ResNet50 and EfficientNetB7 are more effective in detecting maladies in indoor plants regarding accuracy, precision, recall, and F1 score. Our Android application enables the early detection of common diseases that affect indoor plants, particularly those on fashionable balconies, and provides solutions by utilizing ResNet50's advanced image processing techniques. |
| format | Online |
| id | ojs-156 |
| institution | My University |
| language | eng |
| publishDate | 2024 |
| publisher | Jahangirnagar University |
| record_format | ojs |
| spelling | ojs-1562025-03-02T15:38:38Z GreenGuard: : An Android-Based Application for Early Disease Detection of Indoor Plant Rahman, Md. Mahmudur Tumpa, Samira Akter Indoor Plant Disease Detection Deep Learning ResNet50 Android App Image Processing Numerous individuals like the hobby of taking care of indoor plants, which provides both aesthetic and health benefits. However, they may be susceptible to a variety of disorders, as is the case with other plants. Manually identifying plant diseases is a time-consuming, error-prone, and unreliable process that impedes the ability to effectively identify and prevent them. The challenges can be surmounted by the early and precise detection of interior plant diseases by implementing new technologies such as Deep Learning and Machine Learning . In this research, we introduce 'GreenGuard,' a revolutionary solution for indoor plant devotees. This study employs critical deep-learning models to identify plant diseases, including ResNet50, VGG16, EfficientNetB0, EfficientNetB5, and EfficientNetB7. Models such as ResNet50 and EfficientNetB7 are more effective in detecting maladies in indoor plants regarding accuracy, precision, recall, and F1 score. Our Android application enables the early detection of common diseases that affect indoor plants, particularly those on fashionable balconies, and provides solutions by utilizing ResNet50's advanced image processing techniques. Jahangirnagar University 2024-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Conference Proceedings Submission application/pdf http://journals.juniv.edu/index.php/jit/article/view/156 10.59185/jit.v13i01.156 Journal of Information Technology; Vol. 13 No. 01 (2024); 1-20 eng http://journals.juniv.edu/index.php/jit/article/view/156/111 Copyright (c) 2024 Journal of Information Technology |
| spellingShingle | Indoor Plant Disease Detection Deep Learning ResNet50 Android App Image Processing Rahman, Md. Mahmudur Tumpa, Samira Akter GreenGuard: : An Android-Based Application for Early Disease Detection of Indoor Plant |
| title | GreenGuard: : An Android-Based Application for Early Disease Detection of Indoor Plant |
| title_full | GreenGuard: : An Android-Based Application for Early Disease Detection of Indoor Plant |
| title_fullStr | GreenGuard: : An Android-Based Application for Early Disease Detection of Indoor Plant |
| title_full_unstemmed | GreenGuard: : An Android-Based Application for Early Disease Detection of Indoor Plant |
| title_short | GreenGuard: : An Android-Based Application for Early Disease Detection of Indoor Plant |
| title_sort | greenguard an android based application for early disease detection of indoor plant |
| topic | Indoor Plant Disease Detection Deep Learning ResNet50 Android App Image Processing |
| topic_facet | Indoor Plant Disease Detection Deep Learning ResNet50 Android App Image Processing |
| url | http://journals.juniv.edu/index.php/jit/article/view/156 |
| work_keys_str_mv | AT rahmanmdmahmudur greenguardanandroidbasedapplicationforearlydiseasedetectionofindoorplant AT tumpasamiraakter greenguardanandroidbasedapplicationforearlydiseasedetectionofindoorplant |