Revolutionizing agricultural productivity with automated early leaf disease detection system for smart agriculture applications using IoT platform
- Title
- Revolutionizing agricultural productivity with automated early leaf disease detection system for smart agriculture applications using IoT platform
- Abstract
- In smart agriculture, identifying plant illnesses early is vital because it prevents diseases from spreading. A novel statistical approach-based plant disease detection system is developed to identify and categorize diseases early. A novel statistical threshold value is utilized to divide apart the sick portion of the leaf, and a co-occurrence matrix with grey levels is employed to gather the properties. The system uses a visual sensor to record leaf images from the field. The system is tested on publicly available datasets and real-time images captured from fields. Classification is carried out using the support vector machine to achieve higher accuracy. Performance metrics like classification and detection accuracy are used to assess the highlighted system’s effectiveness. The suggested method outperforms the existing state-of-the-art methods with an average detection accuracy of 98.43% and classification accuracy of about 99.9%.
- Scientific Type
- غير معروف
- Journal volume
- Article in Press
- Collaboration type
- مشترك
- Publish Date
- July 12, 2024
- Participated Universities (Publication)
-
Alnoor University
- Scopus status
- In Scopus
- Scopus index year
- 2 024
- Scopus quarter
- 1
- Scopus citation score
- 9.600000381
- Clarivate status
- In Clarivate
- Clarivate index year
- 2 024
- Clarivate impafact
- 4
- Pub. Med. status
- Not In PubMed
- Author (Publication)
-
طلال طه علي سلطان
- Journal (Publication)
-
Environment, Development and Sustainability
- Publisher (Publication)
-
Springer Nature
- ISSN
- 1573-2975
- Country (Publication)
-
Netherlands
- Country type
- عالمية
- College (Publication)
-
College of Health and Medical Technologies
- Departement (Publication)
-
Department of Dental Prosthetics Techniques