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

利用动态 LED 照明系统和人工智能推进受控环境农业 (CEA)

• 批准号: BB/Z514330/1
• 负责人: Hail Rihan
• 金额: $ 97.6万
• 依托单位: Plymouth University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FZ514330%2F1
• 关键词: Advancing; Controlled; Environment; Agriculture; CEA

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.

受控环境农业（CEA）在现代农业中具有重要的商业意义。CEA成功的关键因素之一是使用LED（发光二极管）灯具，可以调整以反映自然环境。LED允许操纵光波长，使光能够根据特定的作物需求进行定制。通过调整光线，CEA种植者可以优化植物生长，增强光合作用，并影响各种植物特性，如味道，颜色和营养成分。这种控制水平提高了作物产量、质量和一致性，使CEA成为寻求可持续和高效方法以满足不断增长的全球粮食需求的商业种植者以及对健康和医疗市场感兴趣的人的有吸引力的选择。我们的目标是通过集成动态LED照明系统和人工智能（AI）技术来推进CEA领域。通过利用尖端技术，我们寻求优化植物生长，提高生产力并提高CEA的资源效率。我们的照明系统将连接到分布在植物上方的树冠上的一个照度计（测量光的强度和光谱的仪器）网络。这将与处理传感器数据和管理光输出的高级软件相耦合。这将有助于优化光合作用和生长模式，从而改善植物健康，提高作物产量和质量。我们将使用人工智能来分析CEA设施内的实时环境数据。通过集成传感器，我们将收集有关光照水平和光谱以及其他相关参数的数据。我们还将收集有关植物对光照条件的反应的数据，例如它们如何吸收和反射光线。然后，人工智能系统将做出数据驱动的决策，以调整环境条件，特别是照明以及其他环境条件（温度和二氧化碳）。这将决定我们是否可以最大限度地提高光吸收率，并最小化以最大限度地提高光合作用速率。此外，我们提出的系统将使我们能够根据植物对各种光处理的反应（光谱技术）来检测植物的化学特征。通过精确地调整环境条件，我们可以减少能源使用，实现更好的资源分配，从而节省成本和环境可持续性。拟议的项目将有许多科学和商业应用。它将通过提供一个先进的控制系统，能够控制光谱，无论环境条件如何，使种植灯制造商受益。通过这项研究，我们将有助于下一代LED生长灯。它将通过提供可持续的照明来帮助种植者，促进植物生长和质量，并节省能源。拟议的项目还将对植物在制药行业的潜在用途产生重大影响，因此将使制药公司和种植者受益。开发的系统的好处将不仅限于CEA，而且还将适用于温室行业，因为通过拟议的系统稳定照明条件（强度和光谱）将有助于稳定温室条件下生长的植物的化学成分。