IMDA, with support from Enterprise Singapore (ESG), is calling for Participants to submit proposals to develop solutions or platforms that can help contractors in the construction stage, specifically in the area of project and/or site management. This call aims to result in the development of solutions or platforms that can extract relevant project data from different sources, such as digital platforms and Internet of Things (IoT) sensors, to facilitate better data visualisation across multiple projects as well as empower stakeholders with data-driven decision capabilities in project and site management through the use of Artificial Intelligence and Data Analytics (AI & DA).
The contractors are facing two key pain points in their day-to-day workflow:
- Absence of a single platform that allows contractors to have oversight of multiple projects at any one time. As contractors use multiple digital platforms to manage different activities in a project, fragmented data residing across multiple platforms are often retrieved and aggregated manually.
- Lack of effective data-driven mechanisms to support effective decision making, for more efficient project and site management. As sense-making and reporting are often done manually with processes varying across different projects and teams, data may not be properly analysed to generate useful insights for more optimal decisions.
This presents an opportunity to uncover potential for AI & DA to improve contractors’ internal processes in project and site management. The call will support interested local tech providers with their development, integration and testing efforts to complete the proposed solutions / platforms and seed early adoption in the industry. To ensure a certain level of feasibility, the tech providers must find at least 2 ready end-users (i.e. contractors) that would trial and subsequently deploy the solution on at least 2 live projects to demonstrate the usability and benefits.
Interested companies may register here for more details. All proposals must be submitted by 29 November 2021, 2359 hours.