Standard closed-circuit television (CCTV) collection time extraction of sewer pipes with machine learning algorithm

Xianfei Yin, Ahmed Bouferguene, Hamid Zaman, Mohamed Al-Hussein, Randy Russell, Luke Kurach

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)

Abstract

Closed circuit television (CCTV) is probably one of the most important technologies that is used by municipalities in order to monitor the structural and operational condition of sewer pipes. To be useful, CCTV video footage needs to be collected according to standards, which make such an operation, time consuming especially when pipes have operational issues like debris or tree roots. In this respect, developing benchmarks for data collection can be an important source of information that can improve the efficiency of future surveying campaigns. Computer simulation is an effective method for improving the efficiency of maintenance work schedules. However, CCTV collection data consists of abundant noise (waiting time or defect inspection time) due to the characteristics of pipes in different structural or operational conditions. For example, crawlers equipped with CCTV cameras could be blocked by deposits or serious structural issues in the pipe, which would cost some waiting time for the crawler to proceed with the inspection. In order to extract the standard CCTV collection time, excluding waiting time and defect inspection time a machine learning based approach is proposed in this work in the form of an algorithm commonly known as the Random Sample Consensus (RANSAC). This algorithm is developed to clean the data automatically, arriving at a function of CCTV collection time with two variables (i.e., length of pipe segment and number of taps in the pipe). The results can be fed into a simulation model to imitate the CCTV collection work in future research.

Original languageEnglish
Title of host publicationProceedings of the 36th International Symposium on Automation and Robotics in Construction (ISARC 2019)
Subtitle of host publicationMay 21-24, 2019, Fairmont Banff Springs Hotel, Banff, AB, Canada
EditorsMohamed Al-Hussein
PublisherInternational Association for Automation and Robotics in Construction
Pages107-113
Number of pages7
ISBN (Print)978-952-69524-0-6
Publication statusPublished - 2019
Externally publishedYes
Event36th International Symposium on Automation and Robotics in Construction, ISARC 2019 - Banff, Canada
Duration: 21 May 201924 May 2019
Conference number: 36

Conference

Conference36th International Symposium on Automation and Robotics in Construction, ISARC 2019
Abbreviated titleISARC
CountryCanada
CityBanff
Period21/05/1924/05/19

Keywords

  • CCTV
  • RANSAC
  • Sewer pipes
  • Time extraction

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