Internet of Things (IoT) based monitoring of changing environmental conditions and their effects on our critical infrastructure

Background

Infrastructure, such as bridges, form the backbone of our modern communities, and the reliability and integrity of such physical assets are vital for ensuring national economic activity and prosperity. The UK Government Strategy for National Infrastructure and consequent National Infrastructure Plan recognises ageing of existing bridges as a key challenge for improving the nation’s infrastructure. Most of the UK’s bridges are now deteriorating and are “in-need” of careful attention. Furthermore, bridges do not carry only goods and people, but gas/water pipelines, electric cables etc. Therefore, the consequence of bridge failures could cascade into other areas such as energy and communication.

In recent years, a growing demand has arisen in urban areas around the world for monitoring the precise movement of existing bridges that are subjected to natural hazards (e.g., flooding). Frequent extreme environmental conditions that have not been considered during the initial design of bridges (e.g. buoyancy effects due to flooding, washing out of mortar etc.) can result in their long-term structural degradation, leading to their structural failure (see Figure 1). Such structural failures can be catastrophic and can lead to wider disruption to the interconnected nature of the infrastructure.

Figure 1. At flood conditions, a standing wave flows through a two-span bridge in Milford (Courtesy of Hampshire Department of Transportation)

The research question to be addressed in this PhD would be how meteorological and environmental conditions (e.g. heavy rainfall, windstorms, humidity, extreme temperatures, water level etc.) affect the structural response and rate of deterioration of our critical infrastructures assets, such as bridges. For this purpose, an advanced research framework based on the emerging Internet of Things (IoT) technologies and data analytics will be developed that will strengthen the research partnership between the disciplines of Geography, Computing and Civil Engineering. It is anticipated that making best use of this data from distributed bridge and environment monitoring systems could enhance resilience of our infrastructure and improve sustainability.

Methodology

This PhD project aims to develop a framework for precise monitoring of environmental parameters (e.g. humidity, water level, temperature, wind speed etc) and their effects to the structural integrity of large civil engineering infrastructure. The fundamental concept will build on active research and undertaken already in the School of Civil Engineering as part of UKRICK and previous EPSRC-funded projects undertaken by the led supervisor EP/T001348/1 for understanding ageing effects on our critical infrastructure. The key focus in this PhD will be to simultaneously monitor both environmental parameters and the results of the effect of these perturbations on the structures to better understand the link between them. This will also require an understanding of the environmental characteristics of the bridge context: geomorphological, hydrological and meteorological in order to understand the temporal and spatial context of the measurements.

The partners have been engaged during the project conception stage and they will be engaged throughout the project by the formation of an industry-academia project steering committee that will meet quarterly to review progress and plan for future developments. The partners will be intimately involved at the outset of the project, in helping to define the electrical, mechanical and software specifications for the prototype. This will ensure that the framework developed will be fit-for-purpose for the long-term displacement monitoring programmes that are envisaged. A project web portal will be hosted and maintained by the PhD student to provide all project partners secure online access to the latest research in the laboratory and experimental results from the field trials. The prototypes developed in the project will be applied on live large scale infrastructure assets and will be made available to the industrial partner.

Analysis of the data resulting from the network will allow explicit causal relationships to be developed that link environmental parameters to structural changes and to help understand any thresholds that may be evident in the physical processes. Together with the environmental characteristics of the bridge contexts, inferences regarding the transferability of the results and the application of the network across the UK should be possible. This will provide insights into the possibility of utilising these methods to monitor aging infrastructure more widely and the potential feasibility of its use in early warning systems.

 Objectives:

  • Provide an environmental characterisation of the bridge locations and historical conditions from existing environmental data, including catchments, river flows/levels timeseries, rain gauge data etc.
  • Determine the target design specifications: electrical, mechanical and software interface, for year-long large infrastructure environment and displacement monitoring.
  • Identify and plan the locations to place the active sensors on the infrastructure whose structural characteristics (e.g. stress and strain) needs to be measured and coupled with the environmental parameter sensors (water levels, scour monitors, rainfall etc.).
  • Design and implement a prototype system/framework based on the above objectives.
  • Conduct field trials in different built environmental settings.
  • Verify the suitability of the developed prototype against other techniques such as manual measurements from total stations, local spot flow gauging, as well as against data collected by the Environment Agency and Met Office.
  • Interpret the data obtained and provide suggestions on the structural behaviour of the infrastructure and causal links with environmental parameters and any thresholds that may be evident.

Student profile

The student should have a keen interest in environmental issues with a strong background in earth sciences, environmental sciences, computer science, geography and/or civil engineering related discipline. Strong remote sensing/data management/fieldwork skills are desirable but not essential, as training will be provided during the PhD.

Align with NERC

This project aligns with the NERC since it will contribute to overcoming current limitations regarding our knowledge of the impact of climate into our infrastructure performance, reliability and safety and will allow a reduction in the number of needless interventions to critical infrastructure, and to more sympathetic and appropriate interventions when these are required, saving tax payers’ money. Outputs will contribute to the emerging industry of “big data”, “digital technology” and “Internet of Things (IoT)”. Additionally, this research will contribute towards delivering knowledge, skills and technology that meet the UK’s innovation needs and support economic growth with responsible environmental management. The environmental characterisation of the bridge locations and historical conditions from existing environmental data and studies on dealing with environmental and decision making uncertainty aligns with the NERC’s Environmental Risks to Infrastructure Innovation Programme (ERIIP). Also, research on big data and IoT aligns with NERC’s Digital Environment Strategic Priorities theme.