There are 7 repositories under crop-recommendation topic.
A machine learning based website that recommends the best crop to grow, fertilizers to use, and the diseases caught by your crops.
AI-based voice-assisted Contact Center for assisting Farmers for their problems.
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
An application that provides complete assistance to farmers right from sowing to harvesting. Its features include plant disease detection, crop recommendation, real-time API support for environment analysis, detailed crop-cost analysis, buy/sell/rent farming equipment and an interactive farmers' community.
A machine learning model in python that recommends the best crop to grow based on Soil composition, Ph level, rainfall and geographical location.
Precision Agriculture based ML and DL project (local host deployment) which have features of crop recommendation, fertilizer recommendation and pesticide recommendation.
Developed a machine learning-based crop prediction model to assist farmers in making informed decisions about crop selection, planting, and harvesting.Integrated weather and geolocation APIs along with a web page for simplified user experience.
A platform of machine learning based website that recommends the best crop to grow, fertilizers to use, and the diseases caught by your crops.
The model focuses on predicting the crop yield in advance by analyzing factors like district (assuming same weather and soil parameters in a particular district), state, season, crop type using various supervised machine learning techniques. This helps the farmers to know the crop yield in advance to plan and choose a crop that would give a better yield.
Saathi - Crop recommendation using ML and plant disease identification using CNN and transfer-learning approach
The Crop Management System is a machine learning-based project designed to provide predictions and recommendations for farmers.
AgriCrop is a Crop Recommendation System built on Machine Learning techniques to recommend the best fitted crop for the given condition by the user.
An Intelligent Crop Recommendation system using Machine Learning that predicts crop suitability by factoring all relevant data such as temperature, rainfall, location, and soil condition. This system is primarily concerned with performing AgroConsultant's principal role, which is to provide crop recommendations to farmers.
We propose an Intelligent Crop Recommendation and Yield prediction system using Machine Learning that predicts crop suitability by factoring all relevant data such as temperature, rainfall, location, and soil condition. The Yield is predicted based on the parameters of area of land available, agricultural season and the past observations of yield .
Helping Farmers make informed decisions with Machine Learning ! 👩‍🌾🚜
"Kisaani" is an application that takes required parameters intelligently or from the database of the location (from the cloud) and provides the list of best crops suited for that land. The application should also be able to collect the outcome after cultivation and apply correction as appropriate for further advisories. The details of the crops for the region and conditions are provided. Applications should be interactive, user friendly for farmers (provide local language support) and should provide support in real time.
Explore our tools to make informed agricultural decisions.
Smart Irrigation System
An application for Farmers to recommend them the best types of crops which can be cultivated on a certain piece of land using Soil Image.
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
ML based Smart Crop Recommendation System with Disease Identification, utilizing CNNs. It aids farmers in selecting crops, managing diseases, and boosts productivity by integrating weather and geolocation APIs.
FastAPI backend for CropFusionAI
Farmer assistant system VCET Hackathon 2k22
Crop Recommendation system using Machine Learning that predicts crop suitability by factoring all relevant data such as temperature, rainfall, location, and soil condition. This system is primarily concerned with performing Agro Consultant's principal role, which is to provide crop recommendations to farmers.
A crop recommendation system for the state of Tamil Nadu. Also yield-predictor (approx.) for the recommended crop.
A machine learning model to recommend suitable crops based on soil health conditions.
Crop Recommendation is a web application that suggest/recommend the farmer to which crop to grown his/her field.
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.
This project aims to develop a crop recommendation system using a Random Forest machine learning model. The system uses a dataset containing information about soil type i.e. PH value and weather factors like temperature, humidity and rainfall to recommend the most suitable crops for a given location.
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
Some AIML Projects
YIELTOR is a webpage used by farmers to know the information about which crop is grown at which time to give the best yield and profit from the crop
Cultivating yield with an intelligent crop recommendation system
Crop Recommendation