AgroSmart - The Smart Agriculture

Execution Video: https://github.com/BODDUSRIPAVAN/AgroSmart-The_Smart_Agriculture/assets/104664633/88ad3ff0-8681-4a61-879e-9326bf835945

Project Guide: Mr. T. Chandrasekhar

Our Team:

1. Boddu Sri Pavan (N180606) - Team Lead, AI ML Engineer
2. Bandi Vikram Kumar (N181167) - ML Engineer, Python developer
3. Mannem Pavan Kumar (N180520) - Python developer, Content writer
4. Mallidi Sandhyarani (N181108) - Web developer, ML Engineer
5. Pragada Padma Priya (N180272) - Web developer, ML Engineer

Abstract:

      Agriculture is the primary source in providing food for entire world. Greater than 45% of the world and 70% of the Indian Population relies on agriculture for its livelihood. Around 50% of loss in crop yield is reported due to pests and diseases. Wrong selection of crop leads to soil infertility as well as crop failure. Early prediction of diseases can save crops. To overcome these two major farming challenges, our project presents state-of-the-art models:

1. Crop Recommendation System: to predict suitable crop from the minimum number of environmental features
2. Early Plant Disease Prediction System: to predict plant diseases with the minimum number of architectural parameters

Algorithms proposed:

1. Crop Recommendation System: Random Forest Classifier- 97.05%
2. Early Plant Disease Prediction System: Convolutional Neural Network- 93.61%.

Data resources:

For crop recommendation system [ 2,200 samples ], https://www.kaggle.com/datasets/atharvaingle/crop-recommendation-dataset
For early plant disease prediction system [ 87,867 samples ], https://www.kaggle.com/datasets/vipoooool/new-plant-diseases-dataset

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