Meet CogniView AI. We provide an AI-powered decision-support platform that augment bridge inspector capabilities. The TeamManuel Flores, PhD researcher at the University of Edinburgh specialising in Artificial Intelligence for predictive maintenance and structural health monitoring. Background includes published research in advanced signal and image processing for infrastructure, as well as over five years of experience applying AI in structural health monitoring. During his master’s studies in South Korea, Manuel worked on two industry-related projects, which strengthened his ability to design solutions grounded in practical needs rather than just theory.Yavuz Yardim, Professor Yavuz brings extensive international experience in bridge inspection, having led projects in Turkey, Malaysia, and Albania. He holds a Ph.D. (2008) and M.Sc. (2002) in Structural Engineering from University Putra Malaysia and a B.Sc. in Civil Engineering from the University of Gaziantep, Turkey (1998). His career spans roles as an engineer, investor, and academic across Turkey, Malaysia, Papua New Guinea, Albania, Oman, and the UK. These diverse positions have given him excellent interpersonal and communication skills, along with strong research and industry networks both locally and abroad. ProblemThe problem is justified by the urgent need to modernise infrastructure management in the face of aging bridge assets and workforce shortages which put additional pressure on asset managers to deliver accurate, timely and actionable insights for safe and cost-effective maintenance planning.Solution Our AI-powered decision-support tool can process large volumes of unstructured data, including scanned PDF inspection reports and transform them into actionable insights by quickly identifying common issues and structural traits across a portfolio of assets.How does it work? The tool functions as an intelligent triage assistant. It automatically analyses reports to identify common issues and structural patterns, highlighting potential problems and suggesting their likely root causes. This allows experts to focus their attention where it's needed most, while the final judgment always remains in their hands.This solution reduces manual effort, minimizes variability in assessments and bridges the knowledge gap between experienced and entry-level inspectors. Ultimately, it enables teams to work more productively while maintaining the high standards of safety and reliability required for critical infrastructure.ContactManuel Fernando Flores CuencaYavuz Yardim This article was published on 2025-10-27
