IoT‌ ‌to‌ ‌detect‌ ‌potential‌ ‌landslides‌ ‌on‌to‌ ‌roads‌

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This case study will address:

  • Low cost entry to IoT
  • Exploitation of legacy data, software, hardware, facilities, skills or knowledge;
  • Bequeathing a rich legacy of new or improved data sources, technology, infrastructure, facilities, practices, skills or partnerships.
  • Low and zero carbon futures (energy)
  • Sustainable care and social systems 
  • Sustainable environments
  • Economic/social regeneration (build back better)
  • New business models
  • Driving and supporting strong regional engagement & ecosystems
  • Data sharing ecosystems
  • Development of skills, including: technical, managerial and methods

This Pitch-In-supported project aimed to integrate new IoT technologies to rapidly share vital  information about the potential for landslides with the authorities managing the road network. This was intended to prompt them to take action to reduce the risk of landslides and manage the road network more safely.

Landslides pose a risk to infrastructure such as roads. Typically they occur due to heavy rainfall, erosion and weathering, and although rainfall-induced landslides are relatively small and rare in the UK, they can block roads and railways or affect the embankments on which they sit.   

The Pitch-In project enabled a collaboration between Newcastle University and a range of project partners who manage major road networks in Scotland and the UK, including Transport Scotland; consultancies working on their behalf including BEAR, Geo-Rope and Jacobs; and Cumbria County Council. 

What were the problems or barriers?

The primary barriers to IoT innovation addressed by this project were around the business case and business processes: 

  • There is a lack of understanding of the IoT solutions available to businesses specialising in road management and the value these can bring.
  • There is a lack of understanding in businesses about how to incorporate IoT-based applications into their existing processes.
  • There is a lack of IoT adoption by those involved in the supply chain.

What did you do?

Finding ways to monitor landslides

  • A monitoring system with IoT-enabled sensors was set up on the A83. In recent years, a stretch of the road, which is the main route between Glasgow and Kintyre, has become Scotland’s landslide hotspot, with a total of 20,000 tonnes of debris hitting the road in 15 incidents since 2007. The system was used to provide live information identifying and characterising types of landslide and potential landslide.
  • The system was evaluated to see how it could be used to make changes in the management of slopes near roads. 

What was the result?

This Pitch-In project achieved a permanent move by Transport Scotland to fund and integrate the monitoring system at a key risk hotspot on the A83 – using the equipment, communication designs for live streaming data and workflows. A number of sensors are still in place, and are being used to make operational and strategic decisions about how best to manage potential landslides on the road. 

A partnership and larger follow-up project was developed with Cumbria County Council and the British Mountaineering Council as a direct result of the initial Pitch-In project. A prototype portal for processing rainfall data was implemented. GPS systems are awaiting deployment for full field testing in Cumbria, on behalf of Cumbria County Council. 

The research has been published in two publications: 

The work has also formed an integral part of a Research Excellence Framework (REF) impact case study submitted by Newcastle University.

Lessons learnt

  • Knowledge exchange: Newcastle University was able to use real projects and data to inform its research papers. Industry partners gained the benefit and insights of the landslide monitoring system.
  • Connecting capabilities: Newcastle University brought IoT expertise, particularly relating to sensors. Industry partners, on behalf of Transport Scotland and Cumbria County Council, brought access to real-world sites and the issues they face with landslides when managing the road networks in their respective areas.
  • The project allowed researchers to focus on communicating data about landslides so that those in charge of managing the road networks could plan responses accordingly; having live information about slopes was the key to driving their adoption of the monitoring system.
  • Partners attempted to work on multiple sites. In hindsight, concentrating on only certain activities and in one location might have been more productive.

What’s next?

It is hoped that there will be an extension of the approach used for this Pitch-In project for a potential spin-out  at a number of sites in Cumbria. The council manage a mountainous road network in the Lake District which is prone to landslides, making this a relevant and valuable piece of research.

The work  has directly fed into a successful Scottish Roads Research Board award (£85k) in which a Newcastle research associate will carry out three months of research related to this project.

An Engineering and Physical Sciences Research Council (EPSRC) grant is planned to upscale and roll out Pitch-In findings to multiple sites, using the Pitch-In partners as official partner organisations on the bid.

Dr Stuart Dunning, Newcastle University said:

“Monitoring and preventing landslides at known high-risk, high-value sites is labour intensive with engineering costing millions. The opportunity provided by Pitch-In allowed us to explore the benefits of IoT to manage landslide risk automatically and far more efficiently. 

It has opened doors to new ways of working with real-time technologies. These offer the potential to scale the monitoring of the road network and allow data-informed decision-making to keep cities connected, while minimising the threat to life.”

Contact:

For further information please contact the Principal Investigator for this project, Dr Stuart Dunning, Stuart.Dunning@newcastle.ac.uk

Related projects: 

Managing hazardous slopes using resilient IoT sensors and real-time processing (slopeRIoT)

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