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SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM

Chilli is extensively grown all over the globe and is particularly important as a food. One of the most difficult issues confronting chilli cultivation is the requirement for accurate identification of leaf diseases. Leaf diseases have a negative impact on chilli production quality, resulting in si...

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Main Authors: Chyntia Jaby, Entuni, Tengku Mohd Afendi, Zulcaffle, Kismet, Hong Ping, Amit Baran, Sharangi, Tarun Kumar, Upadhyay, Mohd, Saeedd
Format: Article
Language:English
Published: Penerbit UTM Press 2023
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://ir.unimas.my/id/eprint/44801/1/SMART%20AGRICULTURAL.pdf
http://ir.unimas.my/id/eprint/44801/
https://journals.utm.my/jurnalteknologi/article/view/19884
https://doi.org/10.11113/jurnalteknologi.v85.19884
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spelling my.unimas.ir.448012024-05-20T03:58:25Z http://ir.unimas.my/id/eprint/44801/ SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM Chyntia Jaby, Entuni Tengku Mohd Afendi, Zulcaffle Kismet, Hong Ping Amit Baran, Sharangi Tarun Kumar, Upadhyay Mohd, Saeedd TK Electrical engineering. Electronics Nuclear engineering Chilli is extensively grown all over the globe and is particularly important as a food. One of the most difficult issues confronting chilli cultivation is the requirement for accurate identification of leaf diseases. Leaf diseases have a negative impact on chilli production quality, resulting in significant losses for farmers. Numerous Machine Learning (ML) and Convolutional Neural Network (CNN) models have been developed for classifying chilli leaf diseases under uniform background and uncomplicated leaf conditions, with an average classification accuracy achieved. However, a diseased leaf usually grows alongside a cluster of other leaves, making it difficult to classify the disease. It will be easier for farmers if there is a reliable model that can classify a chilli leaf disease in a cluster of leaves. The aim of this study was to propose a model for classifying chilli leaf disease from both a uniform background and a complex cluster of leaves. Images of diseased chilli leaves are acquired using a low-cost Kinect camera, which include discoloration, grey spots, and leaf curling. The different types of chilli leaf disease are then classified using an improved ShuffleNet CNN model. With a classification accuracy of 99.82%, the proposed model outperformed the other existing models Penerbit UTM Press 2023 Article PeerReviewed text en http://ir.unimas.my/id/eprint/44801/1/SMART%20AGRICULTURAL.pdf Chyntia Jaby, Entuni and Tengku Mohd Afendi, Zulcaffle and Kismet, Hong Ping and Amit Baran, Sharangi and Tarun Kumar, Upadhyay and Mohd, Saeedd (2023) SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM. Jurnal Teknologi, 85 (5). pp. 93-102. ISSN 2180–3722 https://journals.utm.my/jurnalteknologi/article/view/19884 https://doi.org/10.11113/jurnalteknologi.v85.19884
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Chyntia Jaby, Entuni
Tengku Mohd Afendi, Zulcaffle
Kismet, Hong Ping
Amit Baran, Sharangi
Tarun Kumar, Upadhyay
Mohd, Saeedd
SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM
description Chilli is extensively grown all over the globe and is particularly important as a food. One of the most difficult issues confronting chilli cultivation is the requirement for accurate identification of leaf diseases. Leaf diseases have a negative impact on chilli production quality, resulting in significant losses for farmers. Numerous Machine Learning (ML) and Convolutional Neural Network (CNN) models have been developed for classifying chilli leaf diseases under uniform background and uncomplicated leaf conditions, with an average classification accuracy achieved. However, a diseased leaf usually grows alongside a cluster of other leaves, making it difficult to classify the disease. It will be easier for farmers if there is a reliable model that can classify a chilli leaf disease in a cluster of leaves. The aim of this study was to propose a model for classifying chilli leaf disease from both a uniform background and a complex cluster of leaves. Images of diseased chilli leaves are acquired using a low-cost Kinect camera, which include discoloration, grey spots, and leaf curling. The different types of chilli leaf disease are then classified using an improved ShuffleNet CNN model. With a classification accuracy of 99.82%, the proposed model outperformed the other existing models
format Article
author Chyntia Jaby, Entuni
Tengku Mohd Afendi, Zulcaffle
Kismet, Hong Ping
Amit Baran, Sharangi
Tarun Kumar, Upadhyay
Mohd, Saeedd
author_facet Chyntia Jaby, Entuni
Tengku Mohd Afendi, Zulcaffle
Kismet, Hong Ping
Amit Baran, Sharangi
Tarun Kumar, Upadhyay
Mohd, Saeedd
author_sort Chyntia Jaby, Entuni
title SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM
title_short SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM
title_full SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM
title_fullStr SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM
title_full_unstemmed SMART AGRICULTURAL MONITORING SOLUTION FOR CHILLI LEAF DISEASES USING A LOW-COST KINECT CAMERA AND AN IMPROVED CNN ALGORITHM
title_sort smart agricultural monitoring solution for chilli leaf diseases using a low-cost kinect camera and an improved cnn algorithm
publisher Penerbit UTM Press
publishDate 2023
url http://ir.unimas.my/id/eprint/44801/1/SMART%20AGRICULTURAL.pdf
http://ir.unimas.my/id/eprint/44801/
https://journals.utm.my/jurnalteknologi/article/view/19884
https://doi.org/10.11113/jurnalteknologi.v85.19884
_version_ 1800728142876246016
score 13.211869

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