Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT
Agricultural robots; Crops; Image enhancement; Image segmentation; Intelligent systems; Plants (botany); Water waves; Adversarial networks; Agricultural industries; Cluttered backgrounds; Contextual information; Disease detection; Internet of Things (IOT); Maximum accuracies; Maximum sensitivity; In...
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2023
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my.uniten.dspace-259372023-05-29T17:05:38Z Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT Rathinam R. Kasinathan P. Govindarajan U. Ramachandaramurthy V.K. Subramaniam U. Garrido S. 57196621190 57194393495 6603473566 6602912020 57199091461 25959868500 Agricultural robots; Crops; Image enhancement; Image segmentation; Intelligent systems; Plants (botany); Water waves; Adversarial networks; Agricultural industries; Cluttered backgrounds; Contextual information; Disease detection; Internet of Things (IOT); Maximum accuracies; Maximum sensitivity; Internet of things Detection of crop diseases is imperative for agriculture to be sustainable. Automated crop disease detection is a major issue in the current agricultural industry due to its cluttered background. Internet of Things (IoT) has gained immense interest in the past decade, as it accumulates a high level of contextual information to identify crop diseases. This study paper presents a novel method based on Taylor-Water Wave Optimization-based Generative Adversarial Network (Taylor-WWO-based GAN) to identify diseases in the agricultural industry. In this method, the IoT nodes sense the plant leaves, and the sensed data are transmitted to the Base Station (BS) using Fractional Gravitational Gray Wolf Optimization. This technique selects the optimal path for data transmission. After performing IoT routing, crop diseases are recognized at the BS. For detecting crop disease, the input image acquired from the IoT routing phase is then forwarded to the next step, that is, preprocessing, to improve the quality of the image for further processing. Then, Segmentation Network (SegNet) is adapted to segment the images, and extraction of significant features is performed using the acquired segments. The extracted features are adapted by the GAN, which is trained by Taylor-WWO. The proposed Taylor-WWO is newly devised by integrating the Taylor series and WWO�algorithms. The proposed Taylor-WWO-based GAN showed improved performance with a maximum accuracy of 91.6%, maximum sensitivity of 89.3%, and maximum specificity of 92.3% in comparison with existing methods. � 2021 Wiley Periodicals LLC Final 2023-05-29T09:05:38Z 2023-05-29T09:05:38Z 2021 Article 10.1002/int.22560 2-s2.0-85109081271 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109081271&doi=10.1002%2fint.22560&partnerID=40&md5=60b1b93303d85cfc5ad387c1236f7dcb https://irepository.uniten.edu.my/handle/123456789/25937 36 11 6550 6580 All Open Access, Green John Wiley and Sons Ltd Scopus |
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| description |
Agricultural robots; Crops; Image enhancement; Image segmentation; Intelligent systems; Plants (botany); Water waves; Adversarial networks; Agricultural industries; Cluttered backgrounds; Contextual information; Disease detection; Internet of Things (IOT); Maximum accuracies; Maximum sensitivity; Internet of things |
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57196621190 Rathinam R. Kasinathan P. Govindarajan U. Ramachandaramurthy V.K. Subramaniam U. Garrido S. |
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Article |
| author |
Rathinam R. Kasinathan P. Govindarajan U. Ramachandaramurthy V.K. Subramaniam U. Garrido S. |
| spellingShingle |
Rathinam R. Kasinathan P. Govindarajan U. Ramachandaramurthy V.K. Subramaniam U. Garrido S. Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT |
| author_sort |
Rathinam R. |
| title |
Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT |
| title_short |
Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT |
| title_full |
Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT |
| title_fullStr |
Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT |
| title_full_unstemmed |
Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT |
| title_sort |
cybernetics approaches in intelligent systems for crops disease detection with the aid of iot |
| publisher |
John Wiley and Sons Ltd |
| publishDate |
2023 |
| _version_ |
1806424499397066752 |
| score |
13.214268 |