Harvesting Insights: Agri-Tech Analytics
Harvesting Insights is an Agri-tech analytics tool used for precision agriculture by farm management organizations to plan out their crop calendar. This project involved implementing three core models using Sentinel-2 satellite imagery data:
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Farmland Identification
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Crop Yield Prediction
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Crop Type Classification
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In addition, climate change insights from Twitter were integrated to model extreme weather conditions. Leveraging state-of-the-art machine learning algorithms such as Gradient Boosting, GradCAM, and CNN, this tool provides comprehensive analysis and predictions.
The project culminated in the creation of an interactive Agri-Tech dashboard. By incorporating user feedback, the models were refined, achieving a 15% increase in yield prediction accuracy and a 20% improvement in farmland identification accuracy, thereby significantly boosting agricultural decision-making processes.
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This project won the second place in Berkeley Analytics Showcase hosted by University of California, Berkeley.
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