About 70% of world population relies on agriculture. Agriculture covers the large-scale collection of plants, fruits, crops, etc. For continued healthy production, this harvested product should be disease-free. It needs tremendous quantity of labour, expertise within the plant disease, and conjointly need the excessive time interval. Farmers have a lot of trouble detecting and controlling disease with the naked eye. The necessity for simple plant disease detection that would aid in agriculture is aim of this project.

Existing System

The existing system farmers are using for plant disease detection is naked eye and knowledge about plant disease. For doing so, on large number of plants is time consuming, difficult and accuracy is not good. Consulting expert is of great cost. In few countries the farmers don’t have any idea or facility for contacting the experts. By comparing the plants leafs in the agricultural farm land with the stored plant disease symptoms by automation will be cheaper.

What it does

Plantect is a flutter based web application which the user can use to study and know about their plant(whether it is healthy or diseased etc.) The user can analyze this by simply uploading their plant image. These uploaded images are analyzed using Image processing techniques and detected the condition of plants. Since the theme of EcoHacks 2022 was about environment, I felt to create something closely related to the theme. I started analyzing problems and that is how I came across Plant Healthness. New gradeners or famer find it difficult in analyzing the plant health, my Plantect is a solution to all those problem.

How we built it

I build a flutter based frontend web app which has a login facility. Later user can view list of folder of images they uploaded in app. Next I implemented upload image functionality which stores images in firebase storage. For the important part, i e The Image Processing steps during the time-frame of the hackathon I was able to implement image pre processing, image segmentation, and features extraction methods. This all methods are implemented using python in colab for a same image.

Challenges we ran into

Managing the application as a solo hacker tbh. I really found it difficult to race against time-frame of the hackathon. But pulling off all-nighter has paid off cause I was successful enough to implement important features of my ideas.

Accomplishments that we're proud of

  1. Learning and implementing a Flutter project as a beginner in the techstack.
  2. Image upload using firebase storage.
  3. Exploring various image processing techniques by reading various research papers.
  4. Implementing Image processing techniques using python.

What we learned

  1. Flutter web app
  2. Flutter Integration with Firebase
  3. Image processing techniques
  4. How to efficiently manage time

What's next for Plantect

For now the backend and frontend integration is not yet done properly. Even I will try completing all the steps of Image processing and implement a Machine Learning algorithms for better accuracy.

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