The distinguishing factor of INES in this field is that the team of analysts, consisting of mathematicians, physicists, and data engineers, is led by senior civil engineers, specialists in the maintenance and conservation of infrastructure elements. This enables contextualization of the value of data and ensures the models calibration and validation.
Public and private organizations in charge of civil engineering infrastructure maintenance, collect different information from the assets such as: inventory data, existing damages, repair interventions, incidents due to climate exposure or daily operation and more. This information is being collected along the infrastructure lifecycle, creating an important historic register.
INES offers consultancy services to organize such information in databases and enable the application of algorithms linked with machine learning and artificial intelligence techniques to maximize the benefit of its analysis and help in the decision-making process by introducing a predictive approach.
