Noora Al‐Naimi

Papers

Total Citations

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About

Noora Al-Naimi is a researcher at the forefront of intelligent transportation systems and industrial automation, with a specialized focus on leveraging the Internet of Things (IoT) and computer vision for real-time infrastructure monitoring. Her most cited work, "IoT Based on-the-fly Visual Defect Detection in Railway Tracks" (2020), addresses a critical challenge in railway safety: replacing slow, costly, and error-prone manual inspections with an automated, on-the-fly detection system. By integrating IoT sensors with visual analytics, Al-Naimi’s approach enables continuous, high-accuracy identification of track defects—such as cracks or wear—without disrupting train operations. This contribution has garnered 10 citations, reflecting its practical relevance for public safety and maintenance efficiency. Her research bridges the gap between theoretical IoT frameworks and deployable engineering solutions, offering a scalable model for smart infrastructure. Al-Naimi’s work stands out for its direct impact on reducing human error and operational downtime, positioning her as a key innovator in the growing field of intelligent transport and predictive maintenance. Her findings are particularly valuable for students and engineers seeking to apply IoT and machine learning to real-world safety-critical systems.