Farm Tech Solutions Hub

• 

  website features

• 

  website features

• 

  website features

Inspiration

In India, the number of farmers are: 14.5 crores and the number of farmers who are below the poverty line : is 6.9 crores this causes serious socioeconomic problems.

What it does

1.Cost reduction in farming operations. 2.Enhanced market information for decision-making. 3.Sustainable and profitable farming practices. we are trying to help farmers make informed decisions.

How we built it

main features are crop recommendation, pest detection and optimal irrigation technique we used different types of classification models for crop recommendation and the random forest was used as it gave the highest accuracy and for pest detection, we used ANN.

Challenges we ran into

there was no dataset that had very minimal attributes or no technical aspects of farming like nitrogen content etc, so we had to model our own dataset. the size of the RAM provided was very small, so we had to scrape the images and reduce the size of the dataset.

Accomplishments that we're proud of

we created our own dataset. were able to learn docker which we were not knowing prior (thanks to IBMZ guides) were able to run different models of ML/DL.

What we learned

We learned how to create a virtual machine on IBMZ platform Docker for creating a space container for extra space

What's next for Farm Tech Solutions Hub

creating a website that uses our features and use different types of DL models

Built With

• docker
• kears
• python
• tenserflow