AgroIntelli – Smart Agriculture Assistant Powered by AI
Prof .Kalyani Dahikar, Mr.Piyush Hingankar, Mr. Dnyaneshwar Kate, Mr. Chetan Gangasagar, Mr.
Vignesh Ajmire
Assistant Professor, Dept. of I.T. Prof Ram Meghe College of Engineering & Management, Badnera UG UG Student, Dept. of I.T. Prof Ram Meghe College of Engineering & Management, Badnera
UG Student, Dept. of I.T. Prof Ram Meghe College of Engineering & Management, Badnera UG Student, Dept. of I.T. Prof Ram Meghe College of Engineering & Management, Badnera UG Student, Dept. of I.T. Prof Ram Meghe College of Engineering & Management, Badnera Corresponding Author Email: dnyaneshwarkate2020@gmail.com
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Abstract - Agriculture is a fundamental pillar of India’s economy, supporting the livelihood of a large portion of the population. However, farmers frequently encounter several challenges, including uncertain climatic conditions, limited access to timely agricultural information, unstable market prices, and reliance on intermediaries for selling their produce. These factors negatively impact productivity and reduce overall income stability.
This paper reviews existing technological solutions in the agricultural domain and emphasizes the necessity for a comprehensive and integrated smart farming system. To address these challenges, AgroIntelli is introduced as an intelligent agriculture support platform powered by artificial intelligence. The system utilizes machine learning algorithms to assist farmers in making informed decisions related to crop selection, yield prediction, and fertilizer usage. It also incorporates real-time weather updates through external data sources to improve planning and reduce risks.
In addition, the platform features a direct marketing system that connects farmers with consumers, eliminating the need for middlemen and improving profit margins. Through the evaluation of various research studies, this paper identifies the limitations of current systems, such as fragmented functionalities and lack of accessibility. AgroIntelli overcomes these issues by providing a unified, easy-to-use, and efficient solution. The proposed approach contributes to improving agricultural productivity, increasing farmer income, and encouraging sustainable farming practices using advanced digital technologies.
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Key Words: C o m p u t a t i o n a l A g r o n o m y , D a t a - C e n t r i c C r o p M o d e l i n g , A I - E n a b l e d A g r o A d v i s o r y , H a r v e s t O u t p u t P r e d i c t i o n M o d e l s , C l i m a t e - A w a r e C u l t i v a t i o n S y s t e m s , D i g i t a l A g r o E c o s y s t e m , F a r m e r - C e n t r i c D e c i s i o n F r a m e w o r k , D i r e c t F a r m - t o - B u y e r P l a t f o r m s , T e c h - I n t e g r a t e d C u l t i v a t i o n P r a c t i c e s , S u s t a i n a b l e A g r o I n n o v a t i o n
