Artificial intelligence for Iran

Railway networks across the globe play a crucial role in the transportation infrastructure and embody substantial investments. Neglected networks can have dire consequences for asset longevity, schedule performance, and overall safety. To mitigate these risks, Railroads conduct thorough inspections of their mainline network annually and key locations even more frequently. However, traditional manual inspection methods are not only costly and time-consuming but also pose risks to staff and impact schedule performance. Although attempts have been made to modernize the inspection process using machine-vision technologies, these still rely on human inspectors to manually review images, resulting in subjective and labor-intensive practices. This project introduces a groundbreaking approach utilizing Deep Learning algorithms, specifically a Deep Neural Network, to automatically inspect images, offering a solution that overcomes these limitations and revolutionizes railway inspection processes.