Project description
AI technology to detect and predict infrastructure default
Civil infrastructures in the EU are vulnerable to catastrophic events due to aging and the lack of effective and reliable monitoring tools. As the collapse of the Morandi bridge in Genoa in 2018 demonstrated, such events have significant impacts on human health, the economy and environment. As a consequence, the market demand for effective, reliable and affordable structural health monitoring (SHM) systems that can detect and predict catastrophes is rising. The EU-funded RTExD project aims to develop a real-time event detector based on AI technology. The tool will be able to detect infrastructure defects and damages before their manifestation and predict the failure risks. The RTExD detector will be cost-effective because it avoids the replacement of structures.
Objective
The bridge collapse in Genoa (2018) caused 43 deaths, left 600 without home, and cost €200 million to the EU. This is one of many examples of catasrophic events that cause fatalities, financial and environmental damages due to aging infrastructures and insufficient Structural Healt Monitoring (SHM) solutions. Thus, authorities, owners and maintenance managers of large infrastructures have voiced an urgent need for efficient, reliable, cost-effective and autonomous monitoring solutions that would be able to prevent unwanted catastrophes. This demand is boosting the growth of the SHM market – the predicted market size value is €3,9 billion by 2025, which is 3,6 times bigger than in year 2019 (€1,1 billion).
We, at Securaxis, are developing a break-through technology combining predictive real-time acoustic monitoring sensor with our advanced Artificial Intelligence (AI) technology into the Real Time Event Detector RTExD. Since it is acosutic RTExD can detect infrastructure failures even before they are manifested in the external structure. Learning from them the AI layer will be able to predict when this errors willl be produce giving infrastructure mangers enough time to correct potential future failures.
We target various stakeholders along the value chain of the civil infrastructures construction industry. We address customers in the public and the private domain and they range from infrastructure owners, and engineering companies to governmental authorities. Cost-effectiveness will be the main purchasing driver for our customers – installing RTExD on a wind turbine (3MW) would save up to €6,7million instead of replacing the structure.
Through the complection of the project we expect to reach €40 million cumulative revenues and €28 million cumulative profit in the first 5 years of commersialization. Considering a €2.1 million investment during Phase 2, we estimate a return of investment of 11,9% in 2026.
Fields of science
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencescomputer and information sciencesdata science
- engineering and technologycivil engineeringurban engineeringsmart cities
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energywind power
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
1253 VANDOEUVRES
Switzerland
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.