Lack of knowledge of the conditions of the sewer system leads to premature replacement of pipes costing the Danish society approx. 173 million DKK per year and 10.7 billion per year for the OECD countries. The goal of this project is a robot that uses computer vision and AI to automatically inspect the sewer system and report to a dynamic asset management system. The robot will carry a sensor suite, lighting, battery and onboard processing capability for navigation and obstacle avoidance. Data will be off-loaded to a cloud-based solution where AI algorithms will detect and classify abnormalities in a pipe and together with GIS and other data be used to reduce asset repair and maintenance costs. The project will result in a paradigm shift within the field of pipe inspection. This, in turn, opens up new processes for forecasting maintenance of pipelines.
