IJEEDC Animal Disease Prediction Using Artificial Intelligence and Image Processing

Journal Paper

Paper Title :Animal Disease Prediction Using Artificial Intelligence and Image Processing

Author :Abhay Kumar Gaur, Aditya Raj, Sumit Guwalani, Vellapuneni Kasi Rao, Priyank Arora

Article Citation :Abhay Kumar Gaur ,Aditya Raj ,Sumit Guwalani ,Vellapuneni Kasi Rao ,Priyank Arora , (2024 ) " Animal Disease Prediction Using Artificial Intelligence and Image Processing " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 24-29, Volume-12,Issue-6

Abstract : Animal illnesses are a major global hazard to agricultural productivity, livestock health, and economic stability. This dissertation investigates the viability and efficacy of forecasting diseases in eight distinct animal species—cows, buffalos, pigs, sheep, goats, chickens, horses, and ducks—by utilizing AI and image processing approaches. Looking at the growing problems of farmers, they are unable to provide the immediate help and aid to their animals which deals in unwanted casualties due to lack of proper service and support. Other literature works provided foundational knowledge, guiding research methodology, dataset selection, algorithm choice, and interpretation of findings, enhancing the dissertation's credibility and relevance. The results of this study show how AI and image processing methods can be used to reliably and accurately forecast animal diseases. The generated models demonstrated good results in the identification of various diseases based on visual data across the eight animal species under consideration. This dissertation concludes by highlighting the significance of using AI and image processing technology to forecast animal diseases. Veterinarians and livestock farmers can improve early illness detection and minimize possible outbreaks and financial losses by utilizing machine learning algorithms and image analysis tools. Keywords - Animal Illnesses, Farmers' Problems, Early Illness Detection, Outbreaks, Financial Losses

Type : Research paper

Published : Volume-12,Issue-6


	\|		PDF	\|	Viewed - 24	\|	Published on 2024-09-20

Jan. 2025
Submitted Papers	:	80
Accepted Papers	:	10
Rejected Papers	:	70
Acc. Perc	:	12%
Issue Published	:	141
Paper Published	:	1771
No. of Authors	:	4924

Published : Volume-12,Issue-6

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