Plant Doctor

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  Leaf Detection

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  Scrapping of data about disease and its treatment and then convert it to Json.

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  Accuracy of Model

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  Fetching data form disease

Inspiration

In India, a potential share of crop production is lost due to pests and diseases at a time when the country needs not only to raise production but also ensure food security and nutrition for its growing consumption needs. Pests destroying almost one-fourth of crops

What it does

It analyzes plants features & characteristics and predicts the diseases from which it may be suffering from. Alongside, we give details & description of the disease, with its treatment, prevention, and suggestions.

How we built it

Leveraging the power of Computer Vision and Object Recognition (Machine Learning) along with web scraping from various Sewa Kendras and Kisan Helplines, we built a product that analyzes plants features & characteristics and predict the diseases from which it may be suffering from. Alongside, we give details & description of the disease, with its treatment, prevention, and suggestions.

Challenges we ran into

Collecting the dataset to detect the diseases in crops and plants is the biggest challenges we ran into. Also giving the details about treatment and prevention is also a big task using web scraping.

Accomplishments that we're proud of

The accuracy we obtained from this dataset came out to be 95 %, hence showing strong promise of the deep learning approach for disease prediction and nutrients deficiency.

What we learned

We learned how to convert raw datasets into a good Deep Learning algorithm in such small time with good accuracy.

What's next for Plant Doctor

If such platform gets incorporated into Government Agriculture portals and Kisan Sewa Kendra offices as Self Help Machines, more than one-third of diseases can be prevented and one-sixth can be cured well before time. So we try to convince them to give a look at our work.

Built With

• machine-learning
• node.js
• python-rest