10043586Artificial Intelligence driven Emission Tracking PlatformClosedGrant for R&DInnovate UKIn the UK, there are approximately 5.9 million SMEs employing around 16.8 million people with estimated £2.3 trillion in turnover -- serving as backbone of the UK economy. However, these SMEs account for approximately half of total emissions from UK businesses, and it is vital to reduce SMEs emissions in order to achieve UK NetZero target by 2050\. SMEs, unlike large businesses, face a 'major challenge' in transitioning to NetZero as most SMEs are not properly measuring their emissions. According to Peter Drucker "What cannot be measured cannot be improved", therefore, our aim is to support SMEs smooth transition towards NetZero without affecting the productivity by developing a digital tool which can 1) automate emission tracking without additional cost, 2) display an organisation's performance in real-time against their NetZero pledges and industry standards 3) predict and optimise strategies to reduce emission and enable the organisation to achieve NetZero pledges.However, these are not easy to achieve and have the following technical challenges. 1) Data Interoperability: SMEs are collecting and storing the emission data in diverse formats; therefore, the tool should support data interoperability. 2) Automated Emission Tracking: Designing a secure, reliable, novel, state-of-the-art methodology for autonomous emission data tracking without additional infrastructural or deployment cost. 3) Easy-to-Understand Dashboard: Design easy-to-understand visualisation for measuring organisation's performance against their NetZero pledges. 4) Prediction System: Design an intelligent system to predict smart strategies for reducing emissions. We propose a superior AI-driven Emission Tracking platform that can simplify and automate real-time emission tracking to not only help organisations in analysing emission on-the-go and compare it with their NetZero targets but also predict smart strategies using AI to reduce the overall emissions and achieve NetZero compliance. The key innovations of the proposed framework are: 1) The framework can connect to diverse data sources to collect data autonomously and can therefore be readily adopted by academia and industry bringing its advantages to practice. 2) The framework automates transportation and logistics part of the direct supply chain (scope 3) emission tracking without any additional infrastructural costs 3) The framework uses AI to predict smart emission reduction strategies to reduce overall emission and achieve NetZero compliance. The technical deliverables will be: 1) An fully working digital and integrated emission tracking and optimisation system. 2) First User Test-case -- Emission data integration, analysis and reduction using the proposed framework.