Scientific Publication: Towards Automated Pipelines for Processing Load Test Data on an HS Railway Bridge in Spain using a Digital Twin

On the 14th of July 2022, UPC represented ASHVIN at the ISARC 2022, International Symposium on Automation and Robotics in Construction organized in Bogota, Colombia.  UPC, a project partner, presented there a scientific publication entitled “Towards Automated Pipelines for Processing Load Test Data on an HS Railway Bridge in Spain using a Digital Twin”. This […]

Scientific Publication: Closing the Gap Between Concrete Maturity Monitoring and Nonlinear Time-dependent FEM Analysis

On the 14th of July 2022, UPC represented ASHVIN at the ISARC 2022, International Symposium on Automation and Robotics in Construction organized in Bogota, Colombia. UPC, a project partner, presented there a scientific publication entitled “Closing the Gap Between Concrete Maturity Monitoring and Nonlinear Time-dependent FEM Analysis through a Digital Twin. Case Study: Post-tensioned Concrete […]

Groundbreakers in Digital Twining: Integrating and fusing data by Athina Tsanousa, Postdoc Researcher

Meeting with our Groundbreaking Researchers In today’s world, data is a powerful asset that can drive innovation, efficiency, and success across various domains when properly collected, analysed and utilised. In the ASHVIN world, sensor data, data fusion and machine learning enhance the capabilities of digital twins in the construction industry by providing real-time insights, predictive […]

Groundbreakers in Digital Twining: Computer science abilities by Panagiotis Giannakeris, MsC Research Fellow

Meeting with our Groundbreaking Researchers Imagine a world where machines see and learn, paving the way for revolutionary applications. These two abilities, Computer Vision and Machine Learning, play a crucial role in creating intelligent and dynamic digital twins for the construction industry. Their fusion enhances data processing, enables real-time monitoring, facilitates predictive analytics, ensures quality […]

Deliverable 6.6 Availability Of Measured Maintenance Data Of Infrastructure For Public Domain

ASHVIN project’s work package “Social innovation and standardization” (WP6) aims to determine future trajectories of ASHVIN-developed innovations, including standardisation triggering standards to be applied by the market in connection with deploying new innovative privacy-focused practices within the industry. These will enable the project results to be widely used afterwards, thus ensuring a sustainable impact of […]

New Scientific Publication in a Journal: Digital twinning during load tests of railway bridges – case study: the high-speed railway network, Extremadura, Spain

On the 9th of October, 2023, the ASHVIN project was proud to see its research article published in an international scientific journal,  Structure and Infrastructure Engineering, that is dedicated to recent advances in maintenance, management and life-cycle performance of a wide range of infrastructures. The published article is entitled “Digital twinning during load tests of […]

New scientific publication in a journal: A Knowledge Graph-based data integration system for digital twins of built assets

A group of researchers from the Technical University of Catalonia, including Carlos Ramonell, Rolando Chacon, and Hector Posada, have recently published a scientific paper titled “Knowledge Graph-Based Data Integration System for Digital Twins of Built Assets.” This paper was published in a scientific journal, Automation in Construction (Volume 153, December 2023, 105109). The paper is […]

ASHVIN Digital Twin Platform: Join our Open Technical Webinar on the 28th of February!

Join us on the 28th of February at 11:00CET for a one-hour interactive session presenting the ASHVIN technology for all interested stakeholders!  The objective of this session is to enable interested stakeholders to understand what the ASHVIN digital twin solution is and how its target users, essentially the construction site managers, could benefit from the […]

Detecting anomalies and de-noising monitoring data from sensors: A smart data approach

In January 2023, Timo Hartmann (↗️), coordinator of the ASHVIN project and professor at the Technical University of Berlin,  co-authored an article entitled “Detecting anomalies and de-noising monitoring data from sensors: A smart data approach“ that was published in the scientific peer-reviewed journal “Advanced Engineering Informatics”, Volume 55.  The article details that when monitoring safety […]