The agricultural sector faces a growing challenge: reducing the use of artificial nitrogen fertilizers, which are responsible for significant environmental harm, including soil degradation, water contamination, and greenhouse gas emissions. Nitrogen is an essential nutrient for plant growth, but most plants cannot directly utilize atmospheric nitrogen. This is where nitrogen-fixing bacteria play a crucial role---these natural soil microbes convert atmospheric nitrogen into a form that plants can absorb, reducing the need for artificial fertilizers. These bacteria are key components of biofertilizers, providing a sustainable alternative. The UK government has recognized the importance of sustainable farming practices and aims to reduce agricultural emissions while maintaining productivity. In line with Innovate UK's Plan for Action, we are focusing on expanding agri-tech innovation, particularly in regions like Eastern England, which is a critical hub for the UK's agriculture, producing 33% of England's crops, including 96% of sugar beet, 57% of vegetables, and 30% of wheat. Agricultural output in East of England was valued at £5.1 billion in 2019, accounting for a quarter of the English total, highlighting the great market opportunity in this sector (DEFRA). Several efforts have been made globally to reduce reliance on chemical fertilizers, including the development of natural fertilizers and engineered bacteria that can fix nitrogen more efficiently. However, current methods have limitations, often lacking in scalability, efficiency, and adaptability across different soil and crop types. This presents an opportunity to enhance nitrogen fixation capabilities through innovative technologies. Engivent Ltd proposes to develop a novel platform for discovering and enhancing nitrogen-fixing bacteria using advanced microfluidic technology. This platform will enable the identification and optimization of bacteria that can improve nitrogen fixation efficiency, helping reduce the dependence on synthetic nitrogen. Unlike conventional approaches, our platform will provide a scalable solution tailored to the specific conditions of various agricultural settings. The UK public, particularly in the Eastern England region, will greatly benefit from advanced solutions in this area. By enhancing natural nitrogen fixation, farmers can reduce the need for artificial fertilizers, leading to improved soil health, lower production costs, and reduced environmental pollution. Eastern England, being a major producer of key crops like wheat, barley, and sugar beet, will be among the first beneficiaries, helping to maintain the region's leadership within Britain. Additionally, this project will foster local economic growth by creating new jobs and opportunities within the agri-tech sector, further supporting the UK's goals for sustainable development and innovation.

Our project aims to revolutionize greenhouse farming by leveraging advanced technologies used in modern electronic chip manufacturing. We will develop a sophisticated digital twin of a greenhouse, focusing initially on one selected plant type such as pepper or tomato. This digital twin will serve as a dynamic virtual model of the greenhouse environment, accurately simulating plant growth under various conditions and optimizing processes in real time. **Primary Goal**: We aim to gather real-time data on environmental conditions, plant growth, and operational workflows by partnering with a local greenhouse farm. This foundational dataset will monitor variables such as temperature, humidity and soil moisture. Using this data, we will construct a digital twin of the greenhouse, modelling the growth and development of the selected plant type. The digital twin will be validated through iterative testing and calibration against real-world data, ensuring accuracy and reliability. **Secondary Goal**: We are aiming to demonstrate a pilot of robot autonomous navigation within the greenhouse. We will achieve this by purchasing an off-the-shelf robot and integrating it within the digital twin and training its operation. The training from the digital twin will be applied to the physical robot equipped for real-time processing and decision-making. Pilot tests will validate robot navigation, task execution, and overall integration with the digital twin, collecting performance data and feedback for further development. **Technological Integration**: We will utilize the latest computational tools for high-performance AI training and inferencing, allowing us to develop and deploy advanced machine learning models that can predict and optimize plant growth and health. This combination of technologies will enhance operational efficiency and significantly reduce resource use and environmental impact. **Addressing Critical Challenges**: Our approach addresses labour shortages, resource inefficiencies, and the need for sustainable farming practices. For instance, smart farming in Chile has cut water use by 70%, and AI-driven sprayers in California can reduce herbicide use by up to 96%. By automating labour-intensive tasks and optimizing resource use, our project aims to significantly reduce operational costs and environmental impact while enhancing crop yield and quality across farms in the UK and overseas. **Impact and Vision**: The successful implementation of this project will demonstrate the feasibility and benefits of integrating digital twin technology, AI, and robotics in greenhouse farming. Our vision is to create a scalable and sustainable farming system adaptable to various crops and environments, contributing to global food security and sustainable agriculture practices.