Connect suppliers, distributors and consumers to trade local produce.

Software Developement laboratory (6th semester) course's project.

Developed a deep learning model using TensorFlow and CNN to accurately identify diseases in potato plants, optimizing crop health and yield. The model distinguishes between diseases such as early blight, late blight, and healthy plants from images with precision.

FarmFinder: Your Path to Agricultural Success 🌾 Discover tailored farm recommendations, filter by preferences, and access fertilizer insights. Join us in revolutionizing agriculture! 🚀 #FarmFinder

"LetUsFarm: Your Agricultural Hub 🌾 Experience seamless access with our login and signup pages. Navigate through personalized farm recommendations on the home and filter pages, tailored to your needs. Engage with dedicated sections for farmers, advisors, and administrators. Let's cultivate success together! 🚜💻 #LetUsFarm"

Farmify is a Python-based project designed to help farmers with crop disease prediction, crop recommendation, and fertilizer suggestions. It utilizes machine learning models and Flask for web application development.

Scripts and files for Agroforestry Insurance related issues and ideas

AI-based voice-assisted Contact Center for assisting Farmers for their problems.

AI integrated drone with agriculture disease detection capabilities.

A simple yet efficient project to automate and make farming smart.

Machine Learning Project

Kheti Shayak

Flutter app which helps farmers take the right decisions with their crop regarding diseases. Our team's idea for GDSC solution challenge 2024

AgriInsightML: Harnessing ML for advanced crop health analytics, this model processes 26K+ images to deliver 90th percentile Top-K accuracy, optimizing agricultural insurance for smallholder farmers with speed and scale

This project explores underlying factors contributing to farmer suicides in India and facilitating targeted interventions. Using advanced data visualization techniques, this report provides a comprehensive analysis of several factors such as Regional trends and hotspots, causes & correlations etc.

An application that allows farmers to list their yields, and consumers to discover and purchase fresh grown produce. React, TypeScript, Node, Express, MongoDB.

Farmeris backend

This innovative mobile application utilizes Flutter for the front-end interface and Flask for the back-end API. Our app employs advanced image processing techniques to detect and diagnose plant diseases accurately.

Add-project-description-here | Voyage-46 | https://chingu.io/ | Twitter: https://twitter.com/ChinguCollabs

FarmIt is an app made for providers and clients, in order to sell and buy products directly to each other