Project Start: 2017
Duration: 2 years
Target Country: UK
International Partners: 4
The SENSOR and SATELLITE Asset Alert and Management Systems (SSAAMS) is an Innovate UK funded 2 years project started in November 2017. SSAAMS will use geo-analytical techniques to develop online, map-based ASSET MANAGEMENT decision support tools derived from sensor data, calibrated with satellite data and other data sets to monitor and predict areas of high risk where disruption to transport, energy and urban systems might occur. Infrastructure operators will be able to remotely and accurately monitor and assess the factors that affect the condition and long-term stability and resilience of their assets.
A monitoring and alerting system will identify potential and actual ‘failure’ events so asset managers can take proactive action to mitigate a potential event, or to react quickly and precisely to detected failures therefore making the infrastructure assets more resilient and minimise costly future interventions as well as improving the daily lives of citizens.
The project team is a consortium of organisations that have experience in all the areas needed to fulfil the project: LEAD – Amey (infrastructure company), Rezatec (SME satellite data analysts), Senceive (sensor provider) and University of Birmingham (railway, climate change).
This project aims to improve monitoring of assets to minimise failure from landscape hazards, disruptions and thereby reduce maintenance costs and extend asset lifetimes. The outputs of the project will be twofold:
The business need that SSAAMS addresses is the current lack of extensive data for asset monitoring of long, linear infrastructure such as railway earthworks to inform asset managers thereby optimising maintenance budgets and reducing the risk of failures. The most significant causes of transport, energy and urban system failures are terrain motion and flooding which are exacerbated by extreme weather, which is predicted to increase.
Current expensive state-of-the-art techniques for monitoring infrastructure include LiDAR, aerial imagery, tilt metres, traditional in-situ ground instrumentation and distributed acoustic sensing combined with weather forecasting. SSAAMS addresses this problem by exploiting the synergies of well targeted ground based sensors providing continuous accurate data at specific points and the new satellite data, which provides greater spatial data, but at less regular intervals, thereby creating an enhanced/more powerful combined data set.
Asset resilience & cost reductions
