As the global demand for agricultural products increases, Artificial Intelligence (AI) becomes a valuable solution in the precision agriculture era. However, conventional AI solutions limit the scalability and flexibility of the deployment of precision agriculture. In this project, we aim to investigate the deployment solution of AI techniques for precision agriculture. We aim to build a cow monitoring system. In the system, robotic cameras and sensors coordinate to detect and analyze the features and activity of cows.
Specifically, the demonstration system will consist of the following deployment components.
- Component 1 - Camera: We will use an RGB camera to capture the picture and a Time-of-Fly (ToF) depth camera to measure the size of the object. Based on these image data, we will estimate cows’ size, weight, and health condition.
- Component 2 – Robotic: We will use a robotic arm to control the camera to capture photos of the cow from various angles and distances. Because the combination of pictures obtained from different angles and distances can improve the accuracy of image analysis. We will use a remote control vehicle as the mobile platform of the robotic arm.
The content above is an overall description of the project. The detailed research work of the project could be based on further discussion between supervisors and students.
- Pyhon programming
- Machine learning