ADVANCING CONTROLLED ENVIRONMENT AGRICULTURE USING ARTIFICIAL INTELLIGENCE

Controlled Environment Agriculture (CEA), which involves growing crops indoors under controlled growth conditions, for example in vertical farms, offers a sustainable alternative to traditional agriculture. However, there is a gap between the large amounts of data collected in these systems and their effective use to optimize growth conditions and improve resource efficiency and crop growth. This project, a collaboration between Rift Labs and the Norwegian University of Life Sciences (NMBU), aims to bridge this gap by leveraging Artificial Intelligence (AI) to revolutionize CEA. The project goal is to develop intelligent systems that monitor and analyze plant traits and environmental conditions, enabling better adjustments to optimize growing conditions. By processing large datasets, AI will provide better monitoring and feedback, improving crop production while reducing resource use and energy consumption. At the core of the project is the creation of a data pipeline that collects real-time information from sensors and cameras in indoor farming environments. Plant images will be labeled with traits such as leaf count, leaf area, color intensity, and signs of disease. Simultaneously, environmental data—including temperature, humidity, pH, light, CO2, and nutrient levels—will be organized in a time-series format, synchronized with the plant images. This labeled data will be used to train deep learning models that non-invasively monitor plant characteristics. The system will predict harvest times, detect early signs of stress or disease, and optimize resource use, enhancing farm efficiency and sustainability. By the end of the project, Rift Labs and NMBU aim to develop a fully integrated AI system for indoor farms such as vertical farms and smart greenhouses. This will enable more sustainable farming practices, improve crop quality, and reduce operational costs, positioning CEA as a key tool in addressing global food security challenges.

The project aims to integrate AI technology and LED lighting solutions to revolutionize Controlled Environment Agriculture (CEA). Collaborating with the Norwegian University of Life Sciences, Rift Labs will develop an AI-driven system to optimize environmental parameters in vertical farming, focusing on LED lighting efficiency. Real-time data on light intensity, temperature, humidity, and plant growth metrics will be collected using a robust data generation pipeline. Advanced machine learning algorithms will analyze the data to identify patterns and correlations between environmental factors and plant growth outcomes. The system will enable precise monitoring, control, and optimization of environmental conditions, maximizing LED lighting efficiency. Collaboration with experts from technology and plant science departments will enhance research capabilities and facilitate knowledge exchange. The project aims to contribute to scientific understanding of AI's potential in CEA and generate practical outcomes for the industry. By deploying and validating the AI models in real-world vertical farming environments, the project will enhance Rift Labs' core activities, products, and services. The ultimate goal is to create sustainable, efficient, and scalable solutions that address challenges in global food production and contribute to a resilient agricultural industry.