

What if a farmer ๐จโ๐พcould identify crop pests, receive fertilizer recommendations, and estimate crop yield๐พโall from a single AI-powered platform?
Farmers often face critical challenges in identifying crop diseases and pests, selecting the right fertilizer based on soil conditions, and predicting crop yield before harvest. Making the wrong decision at any stage can affect productivity, increase costs, and reduce profits.
To address these challenges, we developed
AgroVision๐ฑAI โ Smart Agriculture๐พ: AI-Driven Pest Prediction, a web-based application that combines Artificial Intelligence and Machine Learning to support smarter farming decisions.
Key Features
โซ๏ธAI-Based Pest Detection๐
Upload a crop/pest image.A CNN model based on MobileNetV2 classifies the pest.
Displays the detected pest, confidence score, severity level, and recommended pesticides.
โซ๏ธSmart Fertilizer Recommendation๐จโ๐พ
Takes crop type, soil type, temperature, humidity, moisture, and NPK values as input.
Recommends the most suitable fertilizer to improve crop health and productivity.
โซ๏ธCrop Yield Prediction๐พ
Predicts expected crop yield using agricultural parameters such as crop type, season, rainfall, area, fertilizer usage, and pesticide usage with a machine learning regression model.
โซ๏ธLocation-Based Weather Updates๐ฆ๏ธ
Displays the current weather conditions based on the farmer's location, helping farmers plan irrigation, fertilizer application, and other agricultural activities more effectively.
The attached video demonstrates the complete workflowโfrom user registration and login to dashboard navigation, AI-based pest detection, fertilizer recommendation, and crop yield prediction.
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7 August 2026 ร 17h15
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