Concrete is a fundamental material in construction due to its strength and durability. However, its performance can vary due to its mixing composition, human error, curing conditions, and environmental factors. Traditionally, assessing concrete strength involves creating sample cylinders at the construction site, transporting them to a lab, storing them in curing facilities for weeks, and then performing destructive tests. This process is both time-consuming and resource-intensive, consuming half of the Quality Assurance Team's resources in the construction industry.
The traditional method also relies on skilled technicians, who are scarce. Errors made by less experienced workers can impact construction quality, leading to potential losses worth billions of dollars annually. Consequently, the construction industry has long sought a non-destructive and accurate method for predicting concrete strength.
CreteInsight, powered by Artificial Intelligence (AI), offers a promising solution. It can analyze various factors affecting concrete strength, such as composition, curing conditions, and environmental influences. By using AI, we created a model that predicts concrete strength accurately without the need for destructive testing which saves time and resources while providing reliable results.
CreteInsight is based on a model that is continuously developed and improved, making predictions even more accurate over time. It can also help identify potential issues early, allowing for timely interventions and adjustments in the construction process. This not only ensures better quality control but also enhances overall project efficiency.