304: Aquaponic Farm Automation

The Aquaponics Farm Automation team focused on creating a robotic farming device that scanned an aquaponics bed of plants and analyzed the collected data. The collected data allowed us to identify plants and predict future growth. The previous team who worked on the project had already built the farm-bot and had started identification of the plants.

We had four primary objectives that were our intended goals for this project. Our first objective was to provide a method to move the farm-bot remotely. Our next objective was using the LiDAR sensor to collect data. Then we needed to set up a cloud storage system to store the data. Our final objective was to create a machine learning model to analyze the data. We used Python scripts to control the farm-bot. The LiDAR already contained an application to visualize data and allowed storage of the collected data. We trained the machine learning model using prior data collected by independent research groups. We stored the data on the cloud, which provided cheap storage of the data and the learning model.