Transportation sector is one of the crucial sectors for global economy and road infrastructure is the backbone of the transport network. Road networks have a direct and substantial impact on people’s lives, and thus it needs for regular maintenance and exhaustive monitoring.
The conventional methods for road condition assessment are labor intensive and often fail to meet the present requirements due to the vast area of road networks to inspected within a limited timeframe. Usage of sensors by automation of road damage detection using high-performance sensors is also taking place at some levels but these options are often costly and sometimes unaffordable.
In this context, using AI driven solutions to assess road network for an automated solution can help in easy and early identification of road defects. It involves usage of technologies like Computer Vision, DeepTech, and Machine Learning.
With the advent of Smartphones and Object Detection techniques in AI, these AI techniques are being used to perform road damage inspection. Computer vision AI software extracts road and street level data and identifies information such as road health, street informatory/warning signage and assets.
A Startup, Roadmetrics.AI, is working on this use case. Users need to simply mount smartphone with a customized data collection mobile app above vehicle’s dashboard which captures an image every 10 feet with the entire view of the road. The image data capture starts automatically with the trip and and stops at the end. A specific route can be selected with a targeted approach.
The image data then is sent into a dedicated system, where algorithms—trained with hundreds of thousands of image data points ensuring a high accuracy and constantly improving— can look for damage to the road surface image by image, classify various stages of road pavement damage. Damages are recorded and transferred again to the app. The privacy is also taken care as sensitive information is automatically removed according to GDPR compliance using customised algorithm.
This approach results in considerable savings in time and resources spent by customers in defect identification. Road defects such as cracks and potholes that are a major problem and result in billions of dollars in repair and maintenance can be accurately detected and updated databases of recorded structural damages can be maintained for further maintenance. Some of the key customers for such products are Governments, Road development authorities, Private parties operating in infrastructure sector.
