GIS-based Infrastructure Management System for Optimized
Response to Extreme Events on Terrestrial Transport Networks
University of Vigo
Norwegian Geotechnical Institute
University of Cambridge
University of Minho
Infrastructure Management Consultants
Infraestruturas de Portugal
Texas A&M Transportation Institute
Case 1: Portugal
Case 2: Spain
Case 3: United Kingdom
Case 4: the Netherlands
1. To identify extreme weather conditions and climate risk 'hot spots' as well as natural threats and human-provoked disasters (e.g. fires in tunnels, accidents, human failure and sabotage) that could lead to disruptions in terrestrial transport networks.
2. To increase the efficiency in the operations that lead to resilient infrastructures through a better understanding of the magnitude of the consequences of the most relevant hazards (both natural and man-made) in Europe.
3. To integrate infrastructure conditions into infrastructure information models (IIM) specifically developed for infrastructure networks.
4. To develop an innovative crowdsourcing concept that uses data from Advanced Driver Assistance Systems (ADAS) together with Floating Car Data (FCD) for real-time traffic monitoring and simultaneous high temporal resolution infrastructure monitoring. Crowdsourcing also includes human sensing concepts by exploiting the data that is being recruited from end users through social media.
5. To develop predictive models for critical infrastructure assets that take into account the measured structural performance and trends registered in the infrastructure information models tackled in Objective 3.
6. To develop and implement a modular GIS-based Infrastructure Management System (GIS-IMS) that integrates and guarantees the inter communication and the optimal transfer of data between the different inter-dependent modules and described in Objectives 1, 3, 4, 5.
7. To provide Managers and Operators of infrastructure with tools to improve asset management of critical European Transport Routes/Corridors.
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Dr. Belén Riveiro
University of Vigo
School of Industrial Engineering, Universidade de Vigo
CP36310, Vigo, Spain
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his project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement
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