REsilience oriented decision-making Support Technologies for infRAstucture condition raTing
Communication and mobility of people and goods are a key factor for countries development and society well-being and, hence, one of the Sustainable Development Goals for UNs Agenda. Transport Infrastructure relevance is supported by the national and European funds invested every year for new projects and, increasingly, maintenance of existing infrastructure.
Resilience of the Transport Infrastructure is considered a key managing aim, especially significant during maintenance. Resilience analysis considers infrastructure dynamic inner behaviour addressing several aspects summarised in the acronym RAMSSHEP, which stands for Reliability, Availability Maintainability, Safety, Security, Health, Environment conomics and Politics. Within the current societal context, a new concept for resilience-oriented maintenance that efficiently maximizes infrastructure performance is mandatory.
Society, maintenance and performance are an information vector of impacts for predictive maintenance inspections, where practitioners must have as much information as possible to establish the status of infrastructure, asset or asset elements depending on the representation scale.
The general objective of RESTART is aimed to strengthen the maintenance and performance of Transport Infrastructure in order to secure their positive impact to the society growth through the enhancement of Decision-Making procedures by applying objective and quantitative information technologies about condition rating (CR) based on multiscale and multiband observation methods.
Transport Infrastructure Monitoring based on such sensors will allow for early detection of pathologies that will serve as an indicator of risks and hazards, improving infrastructure CR, supporting decision-making and effective planning of mitigation actions.
The main outcome of RESTART consists of an enhanced module for Infrastructure Management Systems that complements the Expert Inspector view on infrastructure asset element condition providing information that is not visible to the human eye, for example, from thermal images and LiDAR sensors through a multiscale and multiband data processing and analysis framework.
RESTART will be applied to a maintenance scenario in Galician infrastructure. Scenario definition is an essential task based on a resilience-oriented methodology that, considering RAMSSHEP, will address the hazards for infrastructure service and condition.
RESTART framework solution will consist of (semi-)automatic analysis based on Machine Learning (ML) and Artificial Intelligence (AI) of several data sources. Such data sources include satellite imagery, Mobile Mapping Systems (MMS) or in situ sensors depending on the scale.
In addition, mitigation actions and status of the scenario will be stored as historic actions that would be taken into consideration when needed. Experts will benefit from the support of RESTART framework as a complement for DM and, thus, contributing to a higher resilience of infrastructure that will result in an efficient lifecycle maintenance. As a result, more adaptable infrastructure will offer an opening for sustainable development and citizen well-being.