Academic Project
AgroDrishti - Smart Vision for Smart Farming
AgroDrishti is a web-based smart farming platform branded as "Smart Vision for Smart Farming." It enables users to input agricultural and environmental parameters to receive machine learning–based crop yield predictions using a Random Forest model. The goal is to enhance understanding of AI-driven technology-driven projects.
Project Challenges
Understanding the farming data and building a model that gives accurate crop yield predictions was one of the biggest challenges. We also worked on storing data securely, connecting the Flask backend with the PostgreSQL database, and making sure the application runs smoothly on both the web and Android.
- Achieving reliable prediction accuracy with limited agricultural datasets
- Designing role-based session auth with admin/user flows
- Extending a single web app into a functional Android APK
- Balancing functionality with aesthetic design
Project Goals
To build a functional prototype that demonstrates effective digital transformation concepts while focusing on user-centric design. To document the development process clearly to support academic evaluation and potential real-world application.
Tech Stack
- Python
- Flask
- HTML/CSS
- JavaScript
- Leaflet.js
- SQLite
- PostgreSQL
- Random Forest Regression(ML)
- Git & GitHub
Timeline
- Research & Planning: Jan - Feb 2026
- Design & Development: Feb - Mar 2026
- Development: Mar - Apr 2025
- Final Presentation: 30th Apr 2025
