ConcreteAI: Smart Concrete Sensors
Project Motivation
Do you know how long it takes concrete to harden?
Concrete is one of the most used construction materials. The cement reacts with water and other ingredients to form a hard matrix that binds the materials together, which will harden (cures) over time, forming a durable stone-like material that is the basis of the buildings and infrastructure we use today. Concrete takes time to harden so that the mould (also known as formwork) can be removed in a timely and safe manner to ensure the continuity of the construction project. If the concrete is not cured and hardened properly, it can lead to catastrophic consequences to the structure integrity. It usually takes 28 days for concrete to fully reach its target strength.
The current process of monitoring concrete strength used by the construction industry is called concrete cube testing. It is used as an indicator of in-place concrete strength. Consultants and the authority will require samples of a few cube specimens from the main batch to be tested to ensure that it meets the intended strength as specified before moving onto more critical operations. These tests are usually performed as early as a few hours and up to 28 days.
Design
ConcreteAI is a smart solution that monitors the concrete hardening process and predicts its strength in real-time. The sensor is targeted at general contractors, concrete suppliers, and precast manufacturers. With ConcreteAI, we hope to improve construction speed and productivity.
Awards
- EG4301A (Ideas to Start-up) Most Investable Start-up Award 2021
- Faculty of Engineering Innovation & Research Award (High Achievement) 2021
- Outstanding Undergraduate Researcher Prize 2021
- NUS Graduate Research Innovation Programme (Run 6)
- NUS Enterprise Practicum Grant
Project Team
Students:
- Chang Qingyang (Civil Engineering, Class of 2021)
- Lim Yun Han (Materials Science & Engineering, Class of 2021)
- Ooi Xi Yi (Computer Engineering, Class of 2021)
- Siow Ming En Isaac (Civil Engineering, Class of 2021)
Supervisor:
- Kuang Sze Chiang, Kevin (ceeksck@nus.edu.sg)