IoT based Automated Plant Disease Classification using Support Vector Machine
Leaf - a significant part of the plant, produces food using the process called photosynthesis. Leaf disease can cause damage to the entire plant and eventually lowers crop production. Machine learning algorithm for classifying five types of diseases, such as Alternaria leaf diseases, Bacterial Bligh...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2021-09-01
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| Series: | International Journal of Electronics and Telecommunications |
| Subjects: | |
| Online Access: | https://journals.pan.pl/Content/121579/PDF/72_2746_Mewada_skl.pdf |
| _version_ | 1818489301624684544 |
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| author | Hiren Mewada Jignesh Patoliaya |
| author_facet | Hiren Mewada Jignesh Patoliaya |
| author_sort | Hiren Mewada |
| collection | DOAJ |
| description | Leaf - a significant part of the plant, produces food using the process called photosynthesis. Leaf disease can cause damage to the entire plant and eventually lowers crop production. Machine learning algorithm for classifying five types of diseases, such as Alternaria leaf diseases, Bacterial Blight, Gray Mildew, Leaf Curl and Myrothecium leaf diseases, is proposed in the proposed study. The classification of diseases needs front face of leafs. This paper proposes an automated image acquisition process using a USB camera interfaced with Raspberry PI SoC. The image is transmitted to host PC for classification of diseases using online web server. Pre-processing of the acquired image by host PC to obtain full leaf, and later classification model based on SVM is used to detect type diseases. Results were checked with a 97% accuracy for the collection of acquired images. |
| first_indexed | 2024-12-10T17:02:14Z |
| format | Article |
| id | doaj.art-3e6c954f610749169dad2b58cc3ed4e2 |
| institution | Directory Open Access Journal |
| issn | 2081-8491 2300-1933 |
| language | English |
| last_indexed | 2024-12-10T17:02:14Z |
| publishDate | 2021-09-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | International Journal of Electronics and Telecommunications |
| spelling | doaj.art-3e6c954f610749169dad2b58cc3ed4e22022-12-22T01:40:33ZengPolish Academy of SciencesInternational Journal of Electronics and Telecommunications2081-84912300-19332021-09-01vol. 67No 3517522https://doi.org/10.24425/ijet.2021.137841IoT based Automated Plant Disease Classification using Support Vector MachineHiren Mewada0Jignesh Patoliaya1Faculty of Electrical Engineering, Prince Mohammad Bin Fahd University, Al Kobhar, Kingdom of Saudi ArabaiCharotar University of Science and Technology, Changa, IndiaLeaf - a significant part of the plant, produces food using the process called photosynthesis. Leaf disease can cause damage to the entire plant and eventually lowers crop production. Machine learning algorithm for classifying five types of diseases, such as Alternaria leaf diseases, Bacterial Blight, Gray Mildew, Leaf Curl and Myrothecium leaf diseases, is proposed in the proposed study. The classification of diseases needs front face of leafs. This paper proposes an automated image acquisition process using a USB camera interfaced with Raspberry PI SoC. The image is transmitted to host PC for classification of diseases using online web server. Pre-processing of the acquired image by host PC to obtain full leaf, and later classification model based on SVM is used to detect type diseases. Results were checked with a 97% accuracy for the collection of acquired images.https://journals.pan.pl/Content/121579/PDF/72_2746_Mewada_skl.pdfplant disease classificationsupport vector machine (svm)graph cutgray-level co-occurance matrix |
| spellingShingle | Hiren Mewada Jignesh Patoliaya IoT based Automated Plant Disease Classification using Support Vector Machine International Journal of Electronics and Telecommunications plant disease classification support vector machine (svm) graph cut gray-level co-occurance matrix |
| title | IoT based Automated Plant Disease Classification using Support Vector Machine |
| title_full | IoT based Automated Plant Disease Classification using Support Vector Machine |
| title_fullStr | IoT based Automated Plant Disease Classification using Support Vector Machine |
| title_full_unstemmed | IoT based Automated Plant Disease Classification using Support Vector Machine |
| title_short | IoT based Automated Plant Disease Classification using Support Vector Machine |
| title_sort | iot based automated plant disease classification using support vector machine |
| topic | plant disease classification support vector machine (svm) graph cut gray-level co-occurance matrix |
| url | https://journals.pan.pl/Content/121579/PDF/72_2746_Mewada_skl.pdf |
| work_keys_str_mv | AT hirenmewada iotbasedautomatedplantdiseaseclassificationusingsupportvectormachine AT jigneshpatoliaya iotbasedautomatedplantdiseaseclassificationusingsupportvectormachine |