TRAMS-Construct - Trustworthy, Responsible AI and ML for construction using aggregated and Secure site data.

The project will assess the feasibility of a platform that collates and pre-processes camera, sensor and meta data feeds from on-site construction. It will support SMEs using trustworthy and responsible Artificial Intelligence (AI) and Machine Learning (ML) to develop solutions for construction contractors managing large sites, focusing on priority use cases (e.g. productivity improvement, smart contracts and dispute resolution).

The feasibility study will assess:

* Requirements for on-site data collation.
* End-to-end collation, storage and processing/use requirements/barriers.
* Site-specific construction management data needs for priority use case solutions.
* Data pre-processing opportunities/requirements.
* Sector and use case specific challenges and benefits facing trustworthy and responsible AI and ML.
* Supporting revenue and business models.

The feasibility study will be led by UK SME **Glideology** (experts in on-site data capture and structuring with a focus on construction) supported by UK digital SMEs with expertise in AI and ML and experience of trust and responsibility issues in the context of process management and immersive environments.

Construction sector RTO BRE will support use case development, feasibility study reporting, stakeholder engagement and consortium building. Leading construction contractors will provide the construction use case context.