The management of infrastructure involves estimating how infrastructure is likely to deteriorate and how demands infrastructure change over time. Increasing amounts of data and increasing modelling capabilities are providing infrastructure managers with improved abilities with which to determine the optimal maintenance and development interventions on infrastructure. Their exploitation requires rethinking the infrastructure management process.
The management of infrastructure involves ensuring that infrastructure meets society’s demands in terms of provided service and the costs to provide service. The ability of infrastructure to meet demands changes over time due to 1) the use and environmental deterioration, and 2) the changing demands of society. The different expertise required to deal with each of these often leads to two divisions inside infrastructure management organisations, i.e. a maintenance division, which deals with deterioration, and a development division, which deals with new demands. Both are constantly trying to determine the best way to obtain the maximum net-benefit from our infrastructure.
How Does Big Data Support Interventions?
To decide when and where to intervene, and what should be done when they intervene, infrastructure managers in both divisions take into consideration many things that vary both spatially and temporally. When planning maintenance interventions on roads, for example, infrastructure managers must estimate the condition of their infrastructure, how and how fast it is likely to deteriorate, the work to be executed, the cost of the intervention, and how traffic will be disrupted during the intervention. When planning development interventions on roads, for example, infrastructure managers must estimate the extent and density of urban growth, changes in demographics, changes in transportation modes, and the extent of changes in noise and pollutants on people living near roads and the environment. Increased ability to make these estimations improve the ability of infrastructure managers to obtain the maximum net-benefit from our infrastructure.
As large and increasing amounts of data become available, infrastructure managers are increasingly relying on computer systems to help them exploit the data to make optimal infrastructure decisions. In order to ensure that this is done as effectively and as efficiently as possible though, work is needed to 1) increase collaboration between infrastructure managers focused on maintenance and those focused on development, 2) develop tools to model the many processes to be considered and huge amounts of data when planning interventions, and 3) develop tools to support infrastructure managers in their decision making.
Recent work in these areas at the infrastructure management group of the institute for construction and infrastructure management at the ETH Zurich include
- the development of a methodology to estimate risk related to road networks due to heavy rainfalls in the EU research project «INFRARISK»,
- the development of a methodology to estimate risk related to railway networks and plan optimal risk reducing interventions in the EU research project «Destination Rail», and
- the development of methodologies to evaluate the net-benefit of constructing flexible infrastructure, i.e. infrastructure that can easily be modified to accommodate multiple futures.
For more information and contact: Prof. Dr. Bryan T. Adey, chair of Infrastructure Management.
