Welcome page for choosing your options
Fill the details about rainfall, soil type etc and click on predict crop
predicted crop will be displayed
Type the crop name and click on the find pesticide button
Pesticides suitable for the crop will be displayed
Enter name of the crop and location and click on find price
Market price of crop will be displayed
Food is something we eat everyday and we get it on our plate only because of the hard work of the farmers. So, we want to help farmers using my computer science knowledge. Our project “AI based support system for farmers” is born from this thought.
What it does
We did some research on internet and came to know about the major problems faced by them and did a project to solve them by combining Machine Learning and Android. Our project does three things
- Predicting best crop that can be grown in given conditions such as temperature, soil moisture, soil type, rainfall, humidity.
- Suggesting pesticides for a particular crop.
- Information about current market price of crop at particular location
How we built it
In order to solve these problems, We developed a machine learning model using KNN algorithm which predicts crop that should be grown based given conditions such as rainfall, temperature, moisture, soil type and humidity as input. We took these five environmental parameters into consideration such as rainfall, temperature, moisture, soil type and humidity of around 30 crops, analysed over 3000 values in dataset and classified into groups, trained a model to predict which crop has best crop yield. Then We developed android application as a prototype using ADT Eclipse which has three modules which are meant for predicting crops, suggesting pesticides for a given crop and displaying current market price of crop based on location.
Accomplishments that we are proud of
We were able to complete most of the project in given time. Our Machine learning model got an accuracy of more than 95%, and we are proud of these things.
What we learned
We learned time management and working under pressure. We learnt methods to improve accuracy of ML Models.
What's next for AI based support system for farmers
- Integrating Android Application with Machine Learning Model
- Adding new features like language translators,
- one click crop recommendation
- In app selling for connecting farmers to direct consumers.