Designing a Data Schema for AI-Driven Greenhouse and Vertical Farming LED Solutions

Designing a comprehensive data schema and framework for AI-driven LED lighting optimization in greenhouses and vertical farming, with the goal of standardizing agronomic, operational, and environmental inputs into an AI-ready structure. This framework will enable accurate simulations of energy use, crop growth, yield performance, and ROI outcomes, creating a foundation for grower-friendly decision-making tools. By mapping input variables to measurable outputs, the project will guide growers in selecting the most effective lighting solutions that balance productivity, sustainability, and cost-efficiency across diverse controlled-environment agriculture settings.

Designing a Data Schema for AI-Driven Greenhouse and Vertical Farming LED Solutions

The project will produce a structured AI-ready data schema with defined variables, a standardized data collection form for growers, and a mapping framework that links inputs to LED performance metrics. Students will also deliver a comprehensive final report outlining methodology, recommendations, and practical next steps for integrating AI-driven simulations that connect lighting strategies to crop yield, energy efficiency, and ROI in greenhouses and vertical farming. 

UX/UI Design and User Experience Optimization

The objective of this project is to enhance the user interface and overall user experience of our platform. Students will analyze current design challenges, conduct user testing, and deliver wireframes, prototypes, and recommendations to improve accessibility, navigation, and visual consistency.

AI Assistance Prototype Development with Machine Learning

The main objective of this project is to build an AI assistance prototype using machine learning. Students will work on tasks such as dataset preparation, intent recognition, and model training. The goal is to deliver a functional prototype, evaluate performance, and document the development process.