OrgoFarm : Harnessing Artificial Intelligence and Machine Learning to Revolutionize Organic Farming and Direct-to-Consumer Marketing
In the current agricultural landscape, the demand for organic products is surging due to rising health consciousness and environmental concerns. However, organic farmers face significant challenges, including inefficient disease management, unpredictable yield forecasting, and limited market access. OrgoFarm addresses these critical issues by integrating artificial intelligence (AI) and machine learning (ML) technologies to enhance decision-making and streamline operations. The research work involved developing a Farmers Guide for comprehensive assistance, a Marketplace for direct farmer-to-consumer sales, and a Crop Doctor tool utilizing ResNet50 for early disease detection and organic treatment recommendations. Additionally, a Crop Yield Prediction model using LSTM was developed to forecast yields and optimize resource allocation. An AI Virtual Assistant was also implemented to provide real-time farming insights, and a Discussion Forum was created to facilitate knowledge sharing among farmers. The outcomes of the research work include improved disease diagnosis accuracy, enhanced yield predictions, and better price realization for farmers, ultimately promoting sustainability and economic viability in organic farming. By combining AI-driven analytics with a decentralized market model, OrgoFarm transforms the agricultural sector, driving progress and innovation in the industry.
Authors
- James S. Jacob
- Sabu Abraham (ORCID: https://orcid.org/0000-0002-0916-5827)
- K R Dinesh (ORCID: https://orcid.org/0000-0003-1443-3782)
- S. S. George
- S. O
Institutions
- Government Medical College (IN)
Publication Details
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1109/icoeca66273.2025.00117
- Primary Topic
- FinTech, Crowdfunding, Digital Finance
- Type
- article
- Field-Weighted Citation Impact
- 0.00