Advancing Controlled Environment Agriculture (CEA) with Dynamic LED Lighting Systems and Artificial Intelligence

Controlled Environment Agriculture (CEA) holds significant commercial importance in modern agriculture. Among the key factors for CEA to succeed is the use of LED (Light Emitting Diode) light fittings which can be adjusted to reflect natural environments. LEDs allow the manipulation of light wavelengths, enabling light to be customised for specific crop needs.

By tailoring light, CEA growers can optimise plant growth, enhance photosynthesis and influence various plant characteristics, such as taste, colour, and nutritional content. This level of control improves crop yield, quality and consistency, making CEA an attractive option for commercial growers seeking sustainable and efficient methods to meet increasing global food demand and those interested in health and medical markets.

We aim to advance the field of CEA by integrating dynamic LED lighting systems and artificial intelligence (AI) techniques. By leveraging cutting-edge technology we seek to optimise plant growth, increase productivity and enhance the resource efficiency of CEA.

Our lighting system will be connected to a net of spectrophotometers (instruments which measure the intensity and spectra of light) distributed across the canopy above the plants. This will be coupled to advanced software that processes data from the sensors and manages the light output. This will help to optimise photosynthesis and growth patterns, resulting in improved plant health and increased crop yields and qualities.

We will use AI to analyse real-time environmental data within the CEA facility. By integrating sensors, we will gather data on light levels and spectra and other relevant parameters. We will also collect data on plant responses to lighting conditions, for example, how they absorb and reflect light.

The AI system will then make data-driven decisions to adjust the environmental conditions, specifically lighting but also other environmental conditions (temperature and CO2). This will determine if we can maximise light absorbance and minimising to maximise the rate of photosynthesis. Additionally, our proposed system will enable us to detect the chemical profile of plants based on their reaction to various light treatments (spectroscopy techniques).

By precisely tailoring environmental conditions we can reduce energy usage and achieve better resource allocation, resulting in cost savings and environmental sustainability.

The proposed project will have numerous scientific and commercial applications. It will benefit grow light manufacturers by providing an advance control system that is able to control the light spectrum, regardless of ambient conditions. Through this research we will contribute to the next generation of LED grow lights.

It will help growers by providing sustainable lighting that promote plant growth and quality and save energy. The proposed project will also have a substantial impact on the potential use of plants in the pharmaceutical industry and will thus be of benefit to pharmaceutical companies as well as growers. The benefits of the systems developed will not be limited to the CEA but will apply also to the greenhouse industry, since stabilising lighting conditions (intensity and spectra) through the proposed system will help to stabilise the chemical profile of plants grown in greenhouse conditions.