Digital Asset Delivery and Project Management

Automated Cost Estimation and Compliance Checks

Challenge Statement Owner:

M Moser Associates designs and delivers workplace environments that bring out the best in people. By boosting workers’ health, happiness and ability to do great work, they enable organisations to nimbly transform in an ever-challenging world. Since 1981, M Moser has built a reputation for putting people at the centre of everything they do. They stay at the forefront of what drives performance, sharing their research, growing their reach and building new capabilities to meet the needs of their clients.


Despite advances in digitalisation in the built environment sector, many interior design and build projects still rely on manual quantity take-off (QTO) and compliance checks. This process involves many different stakeholders: architects, engineers, quantity surveyors, and consultants. To add to the complexity, there is no standard content or data format amongst them. 

As such, data tracking, sharing, verification and approval is time-consuming and prone to errors. This can result in unnecessary delays and impacts throughout the design, tender, construction and handover stages.

The QTO process is highly manual, involving printed plans, highlighters to mark specific items (like fixtures and furniture), and Excel sheets (to record the counts of each item).

While commercial solutions for automated QTO (such as Togal and Sparkel) are available, they are not designed with Singapore projects and requirements in mind (such as database of commonly used materials, units of measurement, calculation methods) and are thus not as effective in a local context.

M Moser would like to re-invent the way interior spatial data is obtained to dramatically improve efficiency, transforming the traditional process to a truly collaborative and integrative process. AI-based identification and recognition of objects in 2D drawings (for example, DWG and DWF files) and 3D BIM objects (for example, IFC, SketchUp and Revit files) improve the quantification of cost items, cost estimation, and stakeholder coordination process. At the same time, this helps ensure compliance with local requirements.

The Challenge

M Moser is looking for a solution to automate the cost estimation tasks and compliance checks, saving over 80% of man-hours compared to the current manual practice.


The solution should:

  • Detect and identify at least 80% of typical objects (furniture, walls, doors, and rooms);
  • Incorporate a library of objects that is large enough to support the AI applications for QTO and compliance checks throughout design, fabrication, construction, asset delivery, and facility management (AI library development may be phased and prioritised depending on the project development needs);
  • Link common open data (e.g. BuildingSMART Institute’s IFC Schema, Singapore’s IFC-SG) and BIM objects with the Building and Construction Authority’s (BCA) Model Content Requirements (MCR) parameters and its project delivery and compliance checks;
  • As a start, incorporate IFC-SG schema to auto-classify recognised objects based on VML, with primary information to be attached to individual identified objects and trades;
  • Categorise these identified objects with at least 70% accuracy;
  • Provide a visual-based platform for various professional disciplines to work with;
  • Provide a summary of QTO data in formats tailored to various disciplines, allowing professionals to bypass the data organisation phase (especially for large projects) and proceed directly to data review and adjustment. For example:some text
    • Space requirement matching and optimisation for interior designers
    • Headcount and occupancy-related computations on fire services/ACMV for engineers
    • Budget optimisation and value engineering processes for quantity surveyors
  • Enable the data to be viewed on a live visual platform with user-centric UI and UX.

Proof-of-concept (POC)/Pilot Support

M Moser will offer suitable testbed sites in office environments.

In addition, M Moser will provide detailed roadmaps, expert guidance in product development, and a variety of datasets. They are also able to provide support with the manual labelling of datasets and other data-related tasks required to develop the solution.


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Recording from Q&A Session