Raspberry PI for compact autonomous home farm control
This addresses home gardening automation for urban dwellers, but is incremental as it applies existing neural network methods to a specific agricultural control task.
The authors developed an autonomous home farm using a Raspberry Pi to monitor environmental conditions and a neural network to optimize crop growth, resulting in completely autonomous tomato cultivation at home with significantly increased productivity.
This manuscript presented an autonomous home farm for predicting metrological characteristics that can not only automate the process of growing crops but also, due to a neural network, significantly increase the productivity of the farm. The developed farm monitors and manages the following indicators: illumination, soil PH, air temperature, ground temperature, air humidity, CO2 concentration, and soil moisture. The presented farm can also be considered as a device for testing various weather conditions to determine the optimal temperature characteristics for different crops. This farm as a result is completely autonomous grows tomatoes at home.