As our population ages, there is more demand for housing adaptation for older people, and with disabled adults and children, there is a backlog of grant beneficiaries on local authority waiting lists. The delay is due to waiting time for Occupational Therapists(OT) assessment(RCOT,2023) which can be 573 days(Zhou,2019) or more than 18 months (Investigative-Journalism,2023) when the assessment and approval statutorily should not take more than 6 months(Construction Act,1996). Also, the prevalence of disability rises with age, and as society is ageing, more people require housing that meets their needs. 16 million people(24%) in the UK had a disability in 2021/22\. There is the recognition that the sooner the housing adaptations are done, the greater the preventative benefits, e.g. reducing the risk of falls and associated costs. Hip fractures have negative effects on daily living activities, account for around £2billion of fragility-fractures costs, and increased one-year mortality between 18% and 33% in UK(OHID,2021). The regulations/statutory guidance stipulate that social workers/occupational therapists should be involved in the assessment(Care Act,2014). Therefore, there is an urgent need to enhance the process of assessment to improve applicants' quality of life and reduce pressure on the NHS and care homes. The current system of assessment is outdated(manually done), inefficient and disorganised, leading to delays and sometimes death before assessment. To address this anomaly and enhance the quality of life for our aged and disabled population, this project aims to develop an automated person-centred self-assessment online system through a more integrated and collaborative approach to the assessment, design, and installation of adaptations. The proposed study adopts techniques in advanced software development, Artificial-Intelligence(AI), Machine-Learning(ML), Decision-Support-System(DSS) and cloud-computing to create an innovative tool(OTWISE-AI). It consists of four-elements: (a) AI-enabled DFG Triage assessment of needs (b) Personalised adaptations platform (c) AI-powered Grant Advisor platform (d) Interactive VR-platform for bespoke adaptation

Due to its envisioned benefits of facilitating enhanced collaboration, and subsequent cost, time and carbon improvement, Building Information Modelling (BIM) has become the standard for construction project delivery. This is partly driven by the UK government's mandate for the use of BIM on all centrally procured projects since 2016, which in turns drove the development of various standards, guidelines, and protocols. However, there has been a major gap between the BIM in theory and BIM in practice, with projects failing to achieve the envisioned BIM benefits, because of inconsistency, poor coordination, missing information, and confusion over responsibilities, among others (Wang and Zhang, 2021, Akponeware and Adamu, 2017). To facilitate information consistency and BIM benefit realisation as envisioned by the UK government, this project proposes an intelligent collaborative BIM management platform (digital form of BIM Information Manager) for effective standardization, auto-production, communication and coordination of BIM processes, tasks, documents, and information, among project stakeholders. **It consists of four key functionalities:** **(A)BIM Project Management Decision Support Module (BIM-DSS)**: This common data environment (CDE) platform digitises the roles of BIM information manager and facilitates efficient management of BIM project by automatically: * Assigning BIM functions * Suggesting tasks (to-do) * Facilitating data management * Coordinating information among stakeholders * Facilitating schedule optimisation * Indicating project BIMing compliance status **(B)BIM Workflow Optimisation Manager(BIM-WOM)**: Using Uniclass classification, WOM would structure BIM information requirements in line with ISO 19650, BIM protocol and other standards to facilitate compliance and adequate information production and management. **(C)BIM Document Production Assistant(BIM-Doc)**: This would support automated population of BIM documents and facilitate industry-wide consistency. It would also support automated naming of BIM files in line with ISO 19650\. **(D)Automated BIM Execution Planner(Auto-BEP)**: This would support automated creation of BEP and its associated documentations(such as TIDP/MIDP), thereby facilitating seamless creation of requisite document and enhanced collaboration.

Many barriers such as emotional, social, cultural, circumstantial, dispositional, and motivational issues have hindered effective learning for many pupils, notwithstanding the world-class UK learning environments. For instance, the attainment gap between disadvantaged 16-year-old pupil and their peers is estimated at 19.3months of learning, with the disadvantaged pupils falling behind by about 2months/year. A government report, titled "closing the gap", suggests that, without urgent actions, it will take 50 years to close the attainment gap in schools. This is now worsened by COVID-19 pandemic, which affected the disadvantaged pupils and their peers. The dilemma has called for an urgent need for holistic system for tailoring premium and individualized action plans for pupils in an effectively differentiated manner. Consequently, this project addresses the attainment gaps and mitigate the impacts of COVID disruption on pupils' education through a set of holistic diagnostics system, multilevel performance tracking/management solution, wellbeing program manager, and gap-bridging modules for different personas of ability/inability. EDURIGHT project contains five integrated digital solutions and program of activities as follows: **(1)Vulnerability Diagnostics and Analytics Portal (VUDAP):** Provides schools with platform for generating personalized vulnerability index for individual pupil based on various risks to underperformance, including financial, health, mental and social risks, which have been further compounded by COVID-19\. **(2)Performance Diagnostics and Monitoring Platform (PEDAM):** Would facilitate real-time and ongoing diagnostics of pupils' performance based on learning outcomes at topic levels. It will (i) assign percentage performance/attainment index based on expected learning outcomes at topics, subjects, year, and KS levels (ii) Create differentiated teaching plans for teachers, homeschoolers, and extra-mural learning. **(3)Expert Advisor(Program) with Multi-level Intervention Portal(EXAMIP):** EXAMIP is a pupils, teachers and schools intervention plan and mentorship program of activities that aligns with different vulnerability personas and performance levels(using PEDAM and VUDAP). EXAMIP would offer online, one-on-one, and residential counselling programs. **(4)Gap-bridging Program of Learning (GAPROL):** GAPROL learning platform links VUDAP and PEDAM scores with modules for bridging performance gaps based on learning outcomes at topics, subjects, and year levels. It would contain learning outcomes and modules for bridging attainment gaps identified through each of the pupils' VUDAP and PEDAM indices in a differentiated manner. **(5)Multi-criteria Performance Analytics and Management Platform for School Managers(PAM-BOARD):** Supports school leaderships to perform analytics and generate action plans for enhancing schools' performance by enabling (i) topics, subject and year level performance analytics (ii) internal and external comparison (iii) underlying problem diagnostics (iv) intervention planning.

The survey process of deep principal tunnel-sewers is very tedious, needing sewerage regulation entity be disconnected for 2-months for crucial airing and intercommunication network setup, and survey done by 3-squads for 0.5months (assuming a 4-mile long tunnel), expending 2.5 months in total and over half a million pounds in costs. The environment is also particularly unsafe; it has rodents and other disease-carrying animals and carries harmful solids and chemicals even after airing. More recently, they have been found to contain traces of Corona virus (BBC 2020). All these make it difficult to conduct the required multiple survey annually of each, causing intermittent collapse, blockages, and particularly incessant leaks and associated pollution episodes. Pollution episodes from leaks are big and frequent because there are over 3,500 deep principal tunnel-sewers, to which the over 400,000 miles of sewers are connected to, and from which sewage is transported to treatment stations. The leaks have led to pollution of more than 50% of UK rivers and rising (Environment Agency, 2018). The penalty fee for such leaks are usually huge and hard hitting on revenue, causing tunnel owners to be desperate for alternative survey methods. A popular case is that of Thames Water that was given a £20 million penalty significant and avoidable pollution episodes on the River Thames in 2017 (Environment Agency, 2017). Avoidance comes mainly through frequent surveys that begets quick intervention. Thus, an unmet market need exists for a highly productive (quicker, cheaper and safer) survey system that will engender frequent tunnel-sewers surveys. This project will thus develop a holistic Tunnel-sewer survey system (HS3) that includes a tunnel survey-specific unmanned aerial vehicle (T-suv) and artificial intelligence classification models (AI-CM) that will analyse T-suv's videos for fault-classification and survey reports production. At 2-miles per hour T-suv will produce survey videos of a typical Tunnel-sewer system of circa 4-miles length in 2 hours. HS3's AI-CM will analyse the generated survey videos and produce fault reports in circa 30 minutes.

**DEFINITIONS** **Concept-design:** Design team's initial response to a project brief. **Detailed-design:** A design with full details, developed from approved concept-design **SUMMARY** Due to coronavirus lockdown, UK Construction Total Activity Index dropped to 39.3 in March from 52.6 in February; the steepest fall in construction output in 11-years (IHS-Markit, 2020). Government wants to use the coronavirus crisis as an opportunity "to build the homes" and plans to "build build build" as part of recovery plans for construction industry and wider economy, announcing £5bn infrastructure and £12billion affordable newbuild homes investments (PrimeMinister's office,2020). Unfortunately, current/traditional construction methods are too inefficient to achieve this in the required time as they are mostly responsible for the current record housing backlog/deficit of 4milliom-homes (National Housing Federation,2018; BBC Housing-Briefing,2020; McKinsey & Company,2019), and were way off-track to achieve national infrastructure programme's proposed £650billion projects worth by 2025 Current/traditional construction methods are slow, costly, poor quality and relatively unsafe. Compared to manufacturing industry, its poor productivity has cost UK economy £140billion (including tax) over 20years (Mace,2018). Alluding to the problem, the government backs construction industry in its attempt to emulate manufacturing industry by switching to Design for Manufacture and Assembly (DfMA) (Construction Sector Deal, 2018). DfMA trial projects led to reduction of 60%, 44% and 70%+ in duration, cost and onsite labour respectively, 73% improvement in quality and 80% improvement in overall productivity compared to traditional methods (RIBA,2008). Despite the many gains, efforts towards DfMA approach's wider adoption has been unsuccessful, with less than 5% of designers employing the approach. Research by CIOB, RIBA and AECOM show the lack of adoption is because current designers were trained/taught to design for construction and have practised this method for long. Attempts to use CPD trainings have yielded only slight benefit as designers claim being too busy. However, the pandemic has now meant near zero trainees/designers registering, with the training companies and construction output bearing the brunt This project thus aims to use digital means to encourage a wider DfMA adoption by developing a BIM software plugin that automatically generates DfMA concept-designs based on key building design parameters from client/project brief (e.g. material choice, building use/purpose, etc.) The proposed plugin will use Internet of Things, Blockchain Technology, cloud computing, artificial intelligence algorithms (AIA) and big data analytics and include the following: 1)**Automatic DfMA concept-design generator:** will generate multiple concept-designs based on input parameters. Designs will be editable to achieve 'detailed-design' to suit designers' preference. Designs will be generated using: 1a) Parametric modelling AIAs which will use historic data of former DfMA designs to produce new solutions 1b)Generative design AIAs to improve new solutions, producing many valid high performance but cost effective options. 2)**DfMA component adviser:** will suggest components (e.g. lattice-slab, shell-beams etc.) usable to edit an adopted DfMA concept-design to achieve detailed-design that suits designers' preference. 3)**DfMA component availability and price checker:** will provide information on DfMA components prices, delivery times, availability, suppliers' locations, etc. 4)**DfMA designs comparison tool:** will compare selected generated/edited designs based on total cost, estimated duration,etc.