Tomato Mosaic Virus Visual Diagnosis(TMVVD)

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  Gilroy Farm

Inspiration

Last year during a school field trip we traveled to a farm in Gilroy where we got to see many different plants, vegetables , and fruits being grown where they would then be sold to other companies where they would be sold at grocery stores. When we got to the tomato section, the entire crop was wiped out and we were informed it was because of viruses that destroyed the crops. We drew inspiration from this and set out to make an accessible cost-effective device using artificial intelligence technology that can detect the Tobamovirus and give farmers advice to stop it from destroying yields of crops and stop the virus from spreading early on.

What it does

The Tomato Mosaic Virus Visual Diagnosis is an accessible cost-effective device using artificial intelligence technology that can detect the Tobamovirus and give farmers advice to stop it from destroying yields of crops and stop the virus from spreading early on.

How I built it

We built our website first by using the Teachable Machine, and inputted images from google for each of the categories (infected with the tomato mosaic virus and not infected with the tomato mosaic virus), then inputted the code into a glitch website and added additional information with the HTML. After some trials, we finally got the machine working on our website. In the end, our result was near perfect.

Challenges I ran into

We ran into many challenges in the process, at the beginning when developing our Teachable machine code we struggled with it a lot trying to embed it into our html site, we realized that we needed to use a public HTML hosting website so we transferred our site on to glitch. Another challenge we faced was in the process of testing when we realized our project wasn't able to detect infected tomatoes. We edited the code and found some code online that we incorporated with our code to make our process for identifying infectious tomatoes less strict and more lenient.

Accomplishments that I'm proud of

In the end our project had a 95% accuracy rate which we are proud off since our hard work paid off.

What I learned

We learned how to operate the teachable machine program, and how to get a massive amount of pictures in order for the AI to learn sufficiently (we used a chrome extension that lets you download all images on a tab), and also about the different coding languages such as html, javascript, and CSS which we weren't that good at before but learned from the documentation in w3schools

What's next for Tomato Mosaic Virus Visual Diagnosis(TMVVD)

In the future, we plan to venture out into other infections as well as being able to get our product out there to more farmers and educate them about the Tobamovirus and its harms.

Built With

• css
• html
• javascript
• teachable-machine