**TRAMS-Enterprise** will develop a consistent, sector-wide framework (rules, guidance) to manage trusted and responsible data, artificial intelligence, and machine learning-based solutions for the construction sector. In doing this, it draws on the requirements, experience and expertise of leading construction contractors and other industry bodies and experts developing AI solutions for construction. It addresses sector-wide bottlenecks limiting the development/adoption/diffusion of AI/ML solutions for on-site construction. In parallel, the project will directly support UK SMEs in further developing AI-based solutions for construction. The development of these solutions has been restricted by factors such as access to construction data (including trust/responsibility-related issues). It will enable these SMEs to develop data pre-processing and AI-based analysis tools per the TRAMS-Enterprise framework, supported by construction sector representatives who will be potential customers. The project will be led by UK SME **Glideology** (collation and pre-processing of visual/camera data from construction sites. Glideology led the TRAMS-Construct Phase 1 feasibility study, which defined the need for the framework. Glideology will be supported by UK SMEs **Unit9** (integrating real-time site data with Building information models; BIM) and **Assentian** (developing AI-based solutions for sectors including construction). **Cranfield University** will support solution development and validation. Construction RTO **BRE** (via industry body 'Constructing Excellence') will coordinate a sector-wide approach to framework development with contractors **BAM Nuttall, Babcock, Skanska** and **Costain** participating as project partners, supporting the development of the framework and specific AI-based solutions developed by the SMEs. BRE will also support Glideology on project management. The main outputs will be: * A working and adopted version of the framework, with potential models for its continued use as a construction industry approach. * Proof-of-concept versions of AI-based solutions developed by UK SMEs. By addressing sector-wide bottlenecks, TRAMS-Enterprise will accelerate the growth of the UK market for digital and AI-enabled construction management solutions.

We are pleased to present our groundbreaking project aimed at revolutionising the construction industry through the development of an innovative AI tool. Our objective is to leverage on-site knowledge and expertise to provide real-time recommendations that optimise the design and construction process. Traditionally, the construction industry relied heavily on human expertise, resulting in time-consuming decision-making processes prone to errors, delays, and cost overruns. Our AI tool disrupts this paradigm by harnessing machine learning algorithms to analyse a wide range of data sources, including speech, text, and BIM models. By identifying patterns and insights in real-time, our tool offers valuable recommendations to site and construction managers. The key innovation of our AI tool lies in its ability to continuously learn from past projects and improve over time. By leveraging this accumulated knowledge, the tool provides increasingly accurate recommendations, driving significant improvements in construction efficiency, cost reduction, and project outcomes. We recognise that the proposed AI tool will operate in the infrastructure sector and thus we will address potential risks associated with the tool through: * adequate risk assessment and mitigation systems; * high quality of the datasets feeding the system to minimise risks and discriminatory outcomes; * logging of activity to ensure traceability of results; * detailed documentation providing all information necessary on the system and its purpose for authorities to assess its compliance; * clear and adequate information to the user; * appropriate human oversight measures to minimise risk; * high level of robustness, security and accuracy. In collaboration with MMC supplier Project Etopia, we will gather data and insights from their construction projects, serving as a valuable use case. This data will be instrumental in training our machine learning algorithms and enhancing the capabilities of our AI tool. Integration into MMC's existing workflows ensures that project managers and team members receive real-time recommendations, facilitating informed decision-making. Our innovative AI tool has the potential to be a game-changer for the construction industry. By leveraging on-site knowledge, harnessing machine learning algorithms, and providing real-time recommendations, our tool significantly improves the efficiency, accuracy, and outcomes of construction projects. We are dedicated to spearheading this technological advancement and eagerly anticipate collaborating with MMC and other industry leaders to drive efficiencies and enhance project outcomes.

CogiGames Home is a VR telerehabilitation platform that enables stroke survivors to exercise in a motivating, data-driven environment powered by award-winning Brain Computer Interface technology. Stroke rehabilitation is a long, frustrating, and lonely journey with staggering costs to the NHS and the UK economy. CogiGames aims to provide a solution to several problem verticals by creating a personalised, multiplayer experience for stroke survivors, getting the expertise and insights of physiotherapists straight into survivors' homes. We will enable patients and physios to harness the power of data, while it gives patients the self-control for their own rehabilitation and the duration and intensity which they desire. CogiGames is a platform which allows stroke survivors to use movement and brain activity to control immersive games for rehabilitation. It leverages consumer immersive hardware and EEG sensors, with our design of a novel low-cost mounting system to allow online play. While users play they can share recordings of their movement exercises so that physiotherapists can check progress. CogiGames' tele-rehabilitation is enhanced with a brain-computer interface (BCI) so patients can participate even if they have more severe movement limitations through Cogitat's movement intent detection system. The solution sets out new data driven opportunities to address the variability in stroke patient conditions and the many different types of rehabilitation exercises they need to do. It does this by supporting games that run independently of movement specifics, while allowing the journaling of key performance measures so that a user can check their progress for their own motivation and for professionals helping them. The resulting data will help guide new patients toward activities that have been more effective, and support further research leveraging brain wave signals for predictive outcomes. In the clinical setting the Cogigames system will provide a resource that is engaging to use for a wide range of disability, will encourage improvement in function through comparison of performance with previous performance and against peers, and improvement in concentration and focus through feedback on attention during the session. The system will encourage therapists to work on hybrid models of face to face and remote input and this will in turn allow therapy to be accessed in higher doses and for longer periods. These benefits, if realised, are capable of making a substantial impact on recovery patterns and on long term disability in stroke survivors.

VICTOR is a new solution that enables construction professionals to fully engage with on-site activity and personnel without having to go to site. It is an immersive, virtual 'environment' that uses a screen 'dashboard' and virtual/augmented reality headset to present live feeds from on-site cameras (and other sensors) and to overlay these with latest data from the project 'digital twin'. Construction contractors are responsible for managing projects across multiple sites that are often geographically widely dispersed. The project-based nature of site construction work means that specialist engineering/managerial staff need to cover multiple sites from a central office. Their attendance on-site needs to be planned in advance (with consequential impacts on task and overall programme progress where urgent input is needed). Travel to and from site is time consuming and expensive as well as having a significant environmental impact. VICTOR emulates the experience of being on-site in near real-time, enabling office-based experts to provide high-quality technical/managerial support to construction sites that can be located anywhere in the world. It takes advantage of the growing use of digital technology on-site such as cameras/scanners for surveying and monitoring site activity, safety and task progress (potentially enhanced by high-speed, low latency 5G communications networks) as well as digital Building Information Modelling (BIM) and project digital twins. VICTOR uses state-of-the-art gaming technology to integrate these data streams to create an immersive experience for the user. The project will develop a minimum-viable-product version of VICTOR for rapid deployment and which can also be enhanced over time as the quantity and quality of on-site visual data increases. VICTOR will be led by UK SME **Unit9** with **Glideology**, supported by leading construction contractor **Ferrovial** and the Building Research Establishment (**BRE**).

With COGIGAME we seek to open new boundaries with _immersive_ _multi-user_ games complemented with _brain-computer interfaces_ (BCI) capable of detecting and signaling drops in participants' cognitive engagement. Our primary aim for these activities is at rehabilitation practice with stroke survivors while allowing social motivating factors through play that does not rely on complex controllers rather brain activation. In brief, we seek to unlock the potential of a healthy subject to be able to play with a recovering family member or friend to motivate compliance in rehabilitation. Stroke is the most common cause of chronic disability in the UK affecting more than 1.3 million people. After hospital discharge post-stroke most stroke survivors receive rehabilitation therapy at home and most are highly motivated toward achieving optimised recovery. As for the population in general, they are also often willing to spend large amounts of time performing physical or cognitive tasks provided these have purpose and/or are enjoyable. Whilst no similar data exists for home-based therapy it is known from dedicated upper limb hospital-based rehabilitation programs that increased amounts of the correct activity can equate to better improvements and that this can continue for months after stroke onset.

"**Bristol City Council** (**BCC**) is a leader in the use of modern methods of construction (MMC)-based housing solutions; an exemplar for the wider UK. Bristol has a range of social and community-led housing developments planned for 2020-21, including **c.458 homes to** be delivered using innovative MMCs provided by a range of manufacturers. BCC views these developments as a unique opportunity for a step-changing '**demonstrator**' project, assembling a unique supply and demand-side collaboration. It will deliver a major programme of integrated innovation in product and manufacturing processes, data capture, testing and assessment across a spectrum of MMC-based solutions, with providers ranging from local start-ups to national companies. Construction costs, whilst essential enabler, are excluded from eligible costs for Innovate UK. The 'momentum resourcing' provided by Innovate UK funding will enable BCC to integrate inter-departmental expertise, addressing council-level barriers to the delivery of new homes in a coordinated manner. It will enable us to create a nationally replicable delivery model that encourages the use of MMC-based solutions in balancing the supply of new homes with growing demand. Building on CLC metrics we will define '**key performance indicators' (KPIs**), benchmarked against existing housing delivery models. KPIs will include social impacts, public perception and occupant experience as well as supply chain efficacy **(respective savings of 50% and 33% in time and cost targeted in line with ISCF targets),** whole-life performance, quality and environmental impact. These KPIs will inform a major programme of data/information capture from participating MMC supply chains. * The main outcome will be a '**council change model**' supported by a **decision-support 'toolbox'**, enabling local authorities across the UK to address development challenges using MMCs and taking account of local issues (social value, procurement, demographics, skills, location, supply chain capacity, economic, technical and environmental), specific development needs, and supply chain capacity. * Project learning and supply chain collaboration will enable suppliers to deliver effective product, process and supply chain innovations; collaboration with BCC will increase confidence in future demand, facilitating capacity planning and investment. Whilst BCC is key to project delivery, the lead partner will be YTKO (a Bristol-based company working closely with BCC) supported by BRE in project administration and coordination. 9 MMC-based housing solution providers are participating. Stakeholders including other councils, the CIH (data shared with the 'Whole life performance' workstream) and other public-sector and commercial bodies."

Awaiting Public Project Summary

"Cities throughout the world face long-term strategic challenges in delivering large-scale physical infrastructure development whilst addressing social and economic changes and challenges. In delivering such major programmes efficiently and effectively it is essential that investment decisions are thoroughly assessed and their impacts properly understood. Decisions need to be taken not only in the context of the specific development area but also that of the wider city, and over the long term. Decision makers need to take account of high-level factors such as changing demographics, political, economic and sustainability drivers, advances in technology etc. They need to understand and react to impacts on existing infrastructure and services, environment and economy as well as social impacts such as health and wellbeing of residents, workers and visitors. Currently 'city systems' are often siloed and, as a consequence, investment decisions can fail to recognise that the city is more than the sum of its parts, potentially leading to errors in infrastructure development that can take decades to correct. PROVIT will address this challenge by developing an investment simulation and optioneering platform that enables decision makers to create urban investment scenarios, interactively assess their impact on the operation of existing systems and established KPIs, and modify the scenarios in order to create an optimised solution. **PROVIT** works by standardising the contribution of elemental insights from different data and model sources subject to a spatial context. We look to rely on the augmented visualisation of rich data. Visualisation of data is selected for its ability to focus consensus between stakeholders and allow optioneering different scenarios each on their mobile devices to gather specific views from each in connection to different specific data insights. PROVIT will build on the recent Innovate UK-funded VISUALISE project which supports effective, efficient management of physical infrastructure assets by integrating, validating and analysing data from discrete asset systems, BIM approaches and emerging 3D mapping enabled by GIS. PROVIT is led by UK SME UNIT9, supported by complementary SME Cartoconsult and other organisations looking to develop innovative IT-based solutions supporting improved data management, decision-making and service delivery in the built environment. Skanska and Hampshire CC (as well as others in a stakeholder group) will participate as representative end users; the potential market is global and opportunities for overseas sales will be considered throughout. Research providers BRE and the University of Cambridge will provide access to an initial pool of predictive urban system models."