AI Use Case
Optimise greenhouse climate environment to maximise production output
Environmental control system for automated greenhouse plant habitats is trained on a dynamic climate model. This then enables it to optimise inputs of energy, moisture and nutrients to maximise plant growth productivity. The need to optimise space utilisation for urban farming helps justify the investment required.
Cost - Optimise resource allocation,Cost - Reduced waiting times
SunSelect~SunSelect enables greenhouse farmers to more accurately forecast their future harvests with machine learning
Time series,Structured / Semi-structured
Machine Learning (ML),ML Task - Prediction - Multi-class Classification,Product Type - Vision ,ML Task - Prediction - Regression,Model Architecture - Convolutional Neural Network (CNN),Product - Data Capture - Sensor IoT,Product - Data Capture - Camera,Product Type - Vision - Image classification,ML Task - Action Selection - Reinforcement Learning ,ML Task - Prediction - Annotation,ML Task - Prediction - Binary Classification