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The Automated Sewer Inspection Robot (ASIR) is a research project that consists of three main parts: An autonomous CCTV-inspection crawler, automatic annotation of the data using computer vision techniques and applying the data for better asset management. The main objective of the project is to extend the lifetime of sewer pipes with 10 %, which today in general are replaced re-maturely. The life extension translates into an annual saving of approx. 24 mil. EUR in Denmark alone.
The Automated Sewer Inspection Robot (ASIR) research project addresses the fact that many utilities companies replace their waste water pipelines significantly earlier than the expected lifetime of 75 years. The reason for this can be many, but a significant contributing factor is lack of knowledge of the pipes physical condition. It is not unusual that TV inspections are performed with a frequency as low as once every 25 year and to be on the safe side pipes are replaced prematurely as a safety precaution. Therefore, a higher inspection frequency makes it possible to replace “just-in-time” and extend the actual lifetime of pipes hereby utilizing the assets more optimal.
If the lifetime of the pipes can on average be extended with as little as 10 % (about 5 years), an estimated annual saving of approx. 24 million EUR / year can be expected in Denmark alone. Besides the large economical savings, the goals of ASIR are also better operation of the sewer system hereby reducing flooding and improving climate adaptation, less CO2 emissions by utilizing the assets for an extended period of time and better working environment for the CCTV-operators.
The aforementioned goals nicely align with the UN sustainable development goals and more precisely sub goals 9.1, 11.3 and 13.1 with emphasis on the latter.
The ASIR project develops an inspection robot that operates autonomously in the sewer, where it performs a periodic inspection with a high frequency of the pipes. The collected data is automatically analysed by computer vision techniques that reports the condition of the pipe according to the Danish standard for TV inspections.
The vast amount of data from the increased inspection frequency is analysed and visualized for the end-users, the utility companies, in an Asset Management software also developed in the project. The purpose is to provide a reliable prioritized list of pipes that needs either repair or replacement. The asset management tool will rely on not only ASIR data but a wide range of available data and utilize state-of-the-art machine learning techniques to give the best prediction of time for replacement that continues to improve accuracy over time with more data and more data. In this way the utility companies can optimize and extend the life of the pipes to ensure most value from their assets.
ASIR is funded by the Innovation Fund Denmark and consists of a consortium with leading universities, industrial partners from both domestic and abroad as well as the three largest utility companies in Denmark: Aalborg University, TinyMobileRobots, Aarhus Water, Innovation Fund, Southern Danish University, HOFOR, VandCenter Syd, FKSSlamson, Inloc Robotics and EnviDan. The funding for the project started in 2018 and ends in 2021.