**Recent incidents underscore the urgency of such innovations.** For instance, on **22 March 2024**, a passenger train **derailed near Grange-over-Sands station** in Cumbria due to a **void opening in the embankment**, causing significant damage to the train and infrastructure, according to **UK Government reports**. In **February 2024**, a railway cutting **failed at Baildon, West Yorkshire**, resulting in the collapse of a section of embankment and highlighting the **vulnerability of rail infrastructure** to hidden ground instability. The **Q-RAIL project** is transforming how the UK **monitors and protects its transport infrastructure** using advanced **quantum sensing**. It addresses a critical challenge: **hidden ground instability** beneath roads, railways, and tunnels, which can cause sudden failures, costly maintenance, and service disruptions affecting millions of passengers and freight users annually. By introducing **ultra-sensitive quantum instruments** capable of detecting early signs of ground movement, Q-RAIL aims to **enhance safety, reduce maintenance costs**, and support a more **reliable, low-carbon transport network**. Q-RAIL focuses on **cold-atom interferometric gravimetry**, a cutting-edge **quantum technology** that measures minute variations in the Earth's **gravitational field**. By cooling atoms near absolute zero and tracking their response to gravity, the technique can identify underground changes such as **voids, water ingress**, or **soil weakening** with high precision. Unlike traditional radar or electromagnetic methods, **quantum gravimetry delivers absolute, drift-free measurements** across all soil types, including reinforced or waterlogged ground. Over a three-month **feasibility study**, the project will define a practical **use case** and an outline **business case** for deploying **portable quantum gravimeters** across UK rail and highway networks. This study will integrate quantum measurements with **TrackGenesis's nanoRail platform**, an AI-based system already used for **predictive infrastructure maintenance**. Together, they will demonstrate how **quantum data** can improve models, **forecast ground movement** more accurately, and support **sustainable maintenance strategies**. The project is led by **TrackGenesis Ltd**, a UK SME specialising in **intelligent infrastructure analytics**, contributing to **sensor modelling and system integration**. **Network Rail** and **National Highways** participate as end-user partners, offering **operational insight** and **validation**. Q-RAIL aligns with the **Department for Transport's innovation programme** and **Mission 5 of the UK National Quantum Strategy (2023)**, which seeks to deploy **mobile, networked quantum sensors** across national infrastructure by 2030\. The project will provide evidence of the **technical and commercial potential of quantum gravimetry**, guiding future prototype demonstrations and reinforcing the UK's leadership in **quantum-enabled transport resilience** and **sustainability**.

**nanoRail** project aims to revolutionise how railway infrastructure is monitored for potential geotechnical risks, such as landslides, subsidence, and soil erosion. By leveraging **satellite-based Interferometric Synthetic Aperture Radar (InSAR)** technology, the system will provide highly accurate and continuous monitoring of ground deformation around rail tracks without needing ground-based sensors or intrusive installations. The system integrates cutting-edge satellite data with **advanced machine-learning algorithms** to predict potential geotechnical failures before they occur. This proactive approach allows railway operators to address emerging risks early, reducing the likelihood of costly emergency repairs and minimising service disruptions. The system also features real-time alerts and an intuitive dashboard, allowing operators to monitor infrastructure stability and take action when necessary. Designed to be scalable and cost-effective, the global monitoring system applies to rail networks, providing a flexible solution for different environments and geographical conditions. The system's reliance on existing satellite infrastructure ensures broad coverage without the need for expensive and disruptive sensor networks. It is a valuable tool for improving rail infrastructure safety and efficiency. Our project will initially focus on a feasibility study to develop and refine the technology, followed by a pilot deployment on a selected railway segment to test and validate its performance. This will lay the groundwork for a full-scale rollout, enabling rail operators to enhance safety, optimize maintenance schedules, and reduce operational costs. This innovative approach aligns with the increasing demand for infrastructure safety. It addresses the rail industry's growing need for non-intrusive, sustainable, and scalable solutions to manage and mitigate geotechnical risks. Using satellite technology and machine learning, our project provides a forward-thinking answer to one of the worldwide critical challenges rail operators face. The Non-Intrusive Geotechnical Stability Monitoring System represents a significant innovation in rail infrastructure monitoring. By utilizing satellite-based InSAR technology and machine learning, the system offers a proactive, scalable, and cost-effective solution to monitoring geotechnical stability around rail infrastructure. The project aligns closely with the competition scope and offers a clear commercial pathway to market, with potential applications across the global rail industry. With the expertise and experience of the lead organisation, this project is well-positioned for success.

Overconsumption of resources is a global issue. To deal with resource depletion and mitigate impending crises, the circular economy (CE) provides an ecosystem by reducing waste via reuse, repair, refurbishment, and recycling the existing materials and products. However, new performance measurements are needed for effective CE management with the increasing complexity of supply chains. We want to address this issue by performing a feasibility study with AI-enabled blockchain technology using fog-computing architecture for CE management to decrease transaction costs, enhance performance and communication along the supply chain, and reduce carbon footprints. The project aims to build an e-waste management system that can respond to supply chain challenges using blockchain technologies. A supply chain can get complicated very quickly, considering each product component has its supply own chain. Blockchain provides a solution to this by establishing transparency in every node of the product's lifecycle. In brief, it is a decentralized list of records or data, known as a block, connected using encryption technology. There are multiple copies of the audit trail for every transaction using blockchain, which will provide the ability to track and reuse/recycle Waste Electric and Electronic Equipment (WEEE). The proposed blockchain-based management solution is designed to be replicated in various sectors to establish transparency and can be easily scaled globally. This may decrease the cost of materials allowing companies to run more efficiently. The practice can also improve customer loyalty and provide additional industry benefits such as saving elements in smartphones that could run out in the next century: * Gallium: Used in medical thermometers, LEDs, solar panels, and telescopes and has possible anti-cancer properties * Indium: Used in transistors and microchips * Yttrium: Used in white LED lights and camera lenses and can be used to treat some cancers * Tantalum: Used in surgical implants, electrodes for neon lights, turbine blades, rocket nozzles and nose caps for supersonic aircraft, hearing aids and pacemakers Therefore, we humbly believe that our solution will be a disruption compared to the conventional ways of how we manage our e-wastes.