Improving Infrastructure Asset Management with Computer Vision

Result! Data, a Netherlands-based consultancy, has developed an application called Spobber to automate the detection of road signs, specifically hectometre signs on Dutch highways and roads, using computer vision. By leveraging various object detection models like YOLOv3, EfficientDet, YOLOv4, and YOLOv5, the app aims to identify these signs accurately and quickly, even at high speeds, such as 100 kilometers per hour. The development involved collecting and annotating a dataset of images, performing data augmentation to simulate various conditions, and using a split of training, validation, and test sets to prevent overfitting. The YOLOv5 model emerged as the most effective due to its speed and efficiency, though the researchers emphasize the importance of diverse training data to ensure models can handle a wide range of scenarios effectively. Future plans include enabling real-time mobile detection of objects to facilitate immediate responses to changes in field conditions.