COTTON PLANT DISEASE DETECTION

Inspiration

Plant diseases often cause serious loss of vegetables and crops.

The study of cotton plant disease involves observation of visual patterns on the leaves.

Detection of plant disease is an important part of cultivation as failure will affect quantity and quality of product and human health.

What it does

Identify the disease in the leave based on training and classification.

Identify the type of disease and pesticide to that disease.

To notify the farmers so that early actions can be taken.

How we built it

Using a convolutional neural network, identify the disease-attacked area in the plant leaf.

To identify the disease and classify the disease in the plant leaf.

The project presents leaf characteristics analysis using image processing techniques for automated vision systems used in the agricultural field.

The stem utilizes image content characterization and supervised classifier type of neural network

Challenges we ran into

The project detects the disease which affects plants most especially, plant leaves.The challenges are:

1. Quantify and measure the severity of the disease on plant leaves.
2. Suggest the appropriate quantity and concentration of fungicides to use on plant leaves based on the disease severity.
3. To make the application more user-friendly.The validity and reliability of the results produced by the systems that are the accuracy is a major concern for the users.

What we learned

I learnt many new skills and languages which has been used such as Html and python. I came to know about plant disease and its disease detection and prevention.

Built With

• css
• html
• javascript
• python