BE:SMART

BE:SMART is a multidisciplinary research group that reimagines how we design, construct, manage, and experience the built environment in the digital age.
We bring together expertise in architecture, engineering, computing, design, and real estate economics to address urgent challenges in urbanization, climate resilience, and digital transformation.

Operating at the intersection of creativity, technology, and sustainability, our work focuses on applied, real-world research that delivers measurable impact. We collaborate closely with industry partners, communities, and policymakers to develop inclusive, data-driven, and sustainable solutions that promote smarter, healthier, and more equitable environments for all.

The Centre for Lean Projects was a research-led initiative at Nottingham Trent University that played a formative role in the development of lean construction research and industry engagement within the University and the broader UK lean construction movement. The Centre served as a focal point for applied research, knowledge exchange, and postgraduate supervision, contributing to NTU’s growing reputation in lean construction, construction management, project delivery, and systems thinking.

The origins of the Centre pre-dated its establishment at NTU and were rooted in the early development of lean construction in the UK during the late 1990s and early 2000s. This period included major national initiatives such as the Construction Lean Improvement Programme (CLIP) and the formation of influential networks linking academia, industry, and policy. These foundations informed the Centre’s research philosophy and collaborative approach.

When Professor Christine Pasquire joined Nottingham Trent University in 2011, she brought with her an established portfolio of lean construction research, PhD students, international collaborations, and strong links to industry and global research communities, including the International Group for Lean Construction (IGLC). Building on this platform, the Centre for Lean Projects was established at NTU to consolidate and extend this work within the University. The annual research showcase offered PhD students the opportunity to present their work to fellow students, faculty, and leaders in the UK construction industry.

During its active period, the Centre supported funded research projects, supervised postgraduate and doctoral researchers, and maintained close partnerships with industry. It also hosted annual lean construction workshops that attracted practitioners and academics from across the UK and internationally, supporting NTU’s commitment to impactful, practice-informed research and external engagement. Pioneers of the lean construction movement, such as Glenn Ballard and Greg Howell, participated in several events sponsored by the Centre.

The Centre for Lean Projects provided a critical intellectual and organisational foundation for subsequent research activity at NTU. Its focus on lean construction, collaborative working, systems thinking, and innovative approaches to project delivery directly informed the evolution of the research themes now embedded within the BE SMART research group. In this way, the Centre for Lean Projects forms a key part of the history and development of BE SMART, contributing to NTU’s ongoing leadership in built environment research.

• Alla Koblyakova
• Emmanuel Manu
• Fouad Mohammad
• Ming Sun
• Patricia Tzortzopoulos
• Song Wu
• Yangang Xing
• Abdullahi Kuta
• Ana Souto Galvan
• Farah Shahrin
• Ehsan Asnaashari
• Abdullahi Kuta
• Richard Bull
• Muhammad Ahmad
• Jason Klous

Panoptic Bridge Management Project: Enhancing Railway Bridge Inspections

Aims to improve the inspection process for railway bridges. The project began in 2019, focusing on developing a digital examination process and a visual inspection system prototype, known as the Asset Visualiser. In 2022, a multi-year programme was initiated to further develop this prototype into a fully functional system integrated with Network Rail’s Intelligent Infrastructure platform.

Challenges in Railway Bridge Management:

• The project was developed in response to several challenges associated with traditional bridge inspections:
• Variability in inspection outcomes – The process relied on individual inspector judgement, which could lead to inconsistent assessments.
• Data quality issues – Inspections often produced incomplete or low-quality data, limiting detailed analysis.
• Inefficiencies – Manual inspection methods were time-consuming and required significant resources.

Development of a Digital Examination Process:

To address these issues, the project developed a digital examination process, leading to a tool that allows for visualising inspection data and conducting virtual examinations. This approach improves data consistency and reduces reliance on subjective assessments. Further improvements have been made with the use of machine learning, which has enabled the development of a model for detecting structural defects. Additionally, a point cloud analysis technique has been incorporated, allowing for detailed surface defect analysis to enhance inspection accuracy.

Current and Future Work:

• Research is ongoing to refine these developments, with upcoming
  studies focused on:
• The digitisation of railway bridges and further integration of AI and Large Language
  Models
• A comparison between digital and traditional inspection methods.
• System integration with the Network Rail Enterprise Asset Management system.
• The project has also secured a Knowledge Transfer Partnership, with plans to adapt
  the technology for broader applications, including highways, national grids,
  and gas pipelines.
• By improving inspection accuracy, efficiency, and data management, the Panoptic Bridge Management project aims to contribute to the modernisation of  railway bridge maintenance.

Integrated virtual wards for ageing well

• Innovate UK KTP
• 01/01/2024-011/01/2026
• £207,378.98
• Industrial Partners: ISTL
• Integrated virtual wards for ageing well use AI-driven digital technologies to deliver hospital-level care at home, supporting older adults with chronic or complex conditions. AI enables personalised care planning, early detection of health deterioration, and coordination across multidisciplinary teams to enhance outcomes and support independent living.