Digital Environment and Asset Management (DEAM)

Our vision

The Digital Environment and Asset Management (DEAM) research group aims to initially connect researchers or those interested in research with diverse disciplines from different departments and schools to explore and investigate novel digital applications and approaches within the built environment and beyond.

The scope of the DEAM Research Group focuses on digitalisation research areas within the built environment, such as Building Information Modelling (BIM), Graphic Information Systems (GIS), occupational hazards and health risks, health and safety, sustainability, energy performance, land and building surveys, etc.

Our aim

The DEAM research group comprises a multidisciplinary research team of scientists and academics focusing on diverse topics, such as BIM, GIS, digital and sustainable developments, Artificial Intelligence (AI), Machine Learning (ML), Information Technologies and Information Management (IT and IM), Quantity Surveying (QS), environmental management, construction management, civil engineering, etc.

The group aims to employ its multidisciplinary nature to generate novel research, guidelines, and standards for digitalisation purposes (such as digital twinning) within the built environment. DEAM also focuses on developing tools and models to assist and manage the built environment sustainability strategies. The latter comprises designing and constructing computer-based tools and applications to enhance the digitalisation processes in the built environment and corresponding domains.

Key projects

Scan-to-BIM

Scan-to-BIM is a broad topic and includes several sub-topics. However, the current research phase focuses on implementing BIM in non-BIM-based ongoing construction projects.

The research focuses on capturing and collecting data from an ongoing construction (The Student Hotel project in Glasgow city centre in this case) and using the raw data to create the 3D model and to embed corresponding and required asset information into the model.

Undergraduate and postgraduate students are involved in the data collection process. Students use the raw data for different purposes in their dissertations.

The initial output of this research at this phase will be journal publications (awaiting data analyses and dissertation submissions).

Scanning Planning Optimisation (SPO)

The SPO research focuses on AL and ML for optimising the location of static laser scanners during the scanning process using 2D drawings. This research is in its early stages (proof of concept), aiming to develop an algorithm that reads 2D drawings, identifies building objects (such as walls, windows, doors, etc) based on their appearance in the drawings, and calculates the optimised locations of the static laser scanner.

Digitalisation within the Quantity Surveying profession

This ongoing research consists of different/multiple aims and objectives, such as using Semantic Web technologies for digitalising the cost estimation, reviewing the terminology used within the QS practices, BIM integration, etc.

GCU Campus Digital Twining

This research focuses on developing a digital twin for the GCU campus for various purposes, such as digital asset management, digital information management, energy performance, integration of digital asset information into digital construction courses, etc.