During infrastructure life cycle, both during construction and during service life, the contractor or the owner can measure different physical parameters (displacements, strains, service loads, temperatures, energy consumption) in order to know if a certain project behaves in the manner envisaged at the design stage. However, few times the data obtained are associated with a certain probability of surpassing a limit state threshold. In most cases, the engineer decides to perform (or not) repair or maintenance tasks in the infrastructure without knowing its actual state based on the information provided by visual inspections and their own intuition and experience. This maintenance procedure causes safety and functionality problems. In addition, inefficient maintenance is associated with a higher cost for infrastructure managers due to severe repairs or excessive energy expenditure. Despite their usefulness, decision support systems have not yet been developed operationally because of the complexity of bringing together advanced and complex scientific, mathematical and practical aspects in areas as dispersed as parameter identification, monitoring, dynamics, energy efficiency and reliability techniques. In addition, due to the high cost of the monitoring systems, only landmark or damaged structures are traditionally instrumented. The purpose of this project is to correct this deficiency by developing a decision support system for managing life cycle of large civil infrastructures (intelligent infrastructure such as bridges, buildings or wind turbines). This will consist of an inverse analysis tool, in which the functional adequacy of the infrastructures associated with certain reliability index (adequacy of structural systems, adequacy of loads, adequacy of energy balance) will be identified. The parameter identification tool will allow quantification of the partial or total functionality of the infrastructure from its static, dynamic or energetic response in non-destructive tests by a parametric mathematical methodology (observability) from low-cost sensor monitoring, linking it with BIM models, allowing benefiting and interacting with the possibilities offered by virtual infrastructure modeling applying BIM methodology. To this end, problems associated with the interoperability of the information flows that allow the updating of the models based on the actual response must also be solved. The great advantage of this method with respect to most of the methods presented in the literature is its versatility, since it allows the updating of any physical property of the model (in this project variables related to structure, actions or energy) The research group has already developed a method of parameter identification by observability techniques for the identification of structures from their static or dynamic response and has applied the BIM methodology for the automatic creation of three-dimensional thermic models in buildings and their monitoring. Undoubtedly, this new decision support system will improve safety and energy efficiency throughout the life cycle of all kind of infrastructures.