Menu Close

Voice-activated AI system could improve construction worker safety, productivity and efficiency

Published by UWE News & Events Voice-activated AI system could improve construction worker safety, productivity and efficiency Construction workers could soon benefit from voice-activated technology that beams real-time audio instructions in their earpiece, and augmented reality (AR) graphics onto their helmet visor, thanks to technology being developed at the University of the West of England (UWE Bristol). Using artificial intelligence (AI), the system will voice and display information, thereby removing the need for walkie-talkies or consulting hard copies of blueprints.The conversational AI technology is being developed by UWE Bristol’s Big Data Enterprise and Artificial Intelligence Laboratory (Big-DEAL) alongside leading construction firms, which include Costain, Winvic Construction Ltd, TerOpta, Enable My…

Graphical User Interface of the Dynamic BIM viewer (image featured, and further explained) in the award-winning paper.

UWE’s Dr Manuel Davila Delgado and author team win the 2019 James Croes Medal from the American Society of Civil Engineers

UWE’s Dr Manuel Davila Delgado and author team win the 2019 James Croes Medal from the American Society of Civil Engineers Dr Manuel Davila Delgado, Dr Liam Butler, Dr Ioannis Brilakis, Dr Mohammed Elshafie and Professor Campbell R. Middleton received the 2019 J. James R. Croes Medal. The medal was awarded on 18 June in Atlanta, USA by the American Society of Civil Engineers (ASCE) for the article:  “Structural Performance Monitoring Using a Data-Driven and Dynamic BIM Environment“, published in the May 2018 edition of the ASCE Journal of Computing in Civil Engineering.The article presents an approach to develop data-driven Digital Twin systems for monitoring the structural performance of infrastructure assets in a dynamic…

Disruptive technology to predict faults on train tracks and in stations

Published by UWE News & Events Disruptive technology to predict faults on train tracks and in stations Train delays could be a thing of the past, thanks to a system that predicts when part of a train track, signalling equipment or other devices at a station are likely to fail. It does this by using thousands of sensors and 3D modelling that taps into big data. The system, currently in development, will also allow engineers to use Augmented Reality (AR) via a smartphone or a Head Mounted Display (HMD) to locate failing components or structure faults and read on-screen instructions in real-time to help them with repairs. The project is…