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##Introduction
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##Introduction##
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FarmEasy is a web-based application designed to assist farmers in managing their crops, inventory, and tasks efficiently. The development of FarmEasy was a collaborative effort by three team members: Pushpdeep Sandhu, Jaspreet Singh, and Varad Pund. The roles and responsibilities were divided to ensure smooth project execution and timely completion.
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##Contribution by Jaspreet Singh (Backend)
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##Contribution by Jaspreet Singh (Backend)##
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Jaspreet Singh was responsible for the backend development of the FarmEasy application. His contributions included implementing the Flask application, database interactions, and backend logic for various features.
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**Files Managed:**
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1. app.py:
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o Developed routes for user authentication, crop management, inventory management, and recommendation systems.
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| ... | ... | @@ -12,8 +13,9 @@ o Implemented session management and password hashing for secure authentication. |
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o Configured the MongoDB connection and defined collections for crops, inventory, and tracker data.
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o Enabled CRUD operations for data management.
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##Contribution by Pushpdeep Sandhu (Frontend)
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##Contribution by Pushpdeep Sandhu (Frontend)##
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Pushpdeep Sandhu was in charge of designing and implementing the frontend components of the FarmEasy application. He focused on ensuring a user-friendly interface and responsive design for various features.
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**Files Managed:**
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1. style.css:
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o Styled the login and signup pages with a modern and responsive layout.
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| ... | ... | @@ -27,9 +29,10 @@ o signup.html: Developed the signup page for new user registration. |
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o dashboard.html: Styled the dashboard with data visualization and task management features.
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o inventory.html, my_crops.html: Created interfaces for managing inventory and crop data.
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##Contribution by Varad Pund (Documentation and Others)
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##Contribution by Varad Pund (Documentation and Others)##
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Varad Pund was responsible for documenting the project and managing auxiliary tasks to ensure project clarity and maintainability.
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Contributions:
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**Contributions:**
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1. Documentation:
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o Created detailed documentation for backend files (app.py, database.py) and frontend files (style.css, dash.css).
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o Explained the functionality of machine learning models in crop_predictor.py and fertilizer_predictor.py.
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