There has been a deficiency on agriculture lately, with this project we aim to solve this problem by creating an autonomous system to help cultivate a home farm.
What it does
In this project we worked on a system that's able to identify several plants with the use of computer vision. This was achieved by using machine learning and color recognition algorithms.
How we built it
The system was built in Raspberry Pi with Python code and the use of Open CV and SK Learn Libraries.
Challenges we ran into
Setting up the Raspberry Pi for this use. Building the models and creating an outline of the plants.
Accomplishments that we're proud of
The code is able to successfully detect through a live feed the plant that is presented to the camera. And accurately identifying and displaying its name.
What we learned
We learned to work with open cv and how to use the sk learn libraries. These libraries were used for computer vision and machine learning respectively. They allowed us to create the models so the code can identify what plant it is and using color recognition to draw an outline of the plant.
What's next for AgroCam
Add more models and make the code more precise. Make the system cognitive mounting the system in a robot that can cultivate and maintain the crops in the home farm.