Pipeline Leak Identification Emergency Robot Swarm (PLIERS)

Ayman Kandil, Ali Darwiche, Reem Qasem, Fatima Matook, Ahmad Younis, Habib Badran, Maryam Bin-Jassem, Ossama Ahmed, Ali Behiry, Mohammed El Abd, Mounib Khanafer

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

Abstract

As cities continue to expand, there has been a substantial increase in demand for factories and sewage systems, which in turn necessitated the need for maintaining the pipeline systems involved. These are typically difficult, dangerous, and expensive to investigate manually by humans, and therefore the use of automated robots is crucial to identifying cracks. Therefore, we propose PLIERS (Pipeline Leak Identification Emergency Robot Swarm). PLIERS is a system consisting of a swarm of robots that are used to investigate pipes for any cracks while communicating with one another as well as a server system. The robots are mounted with cameras to collect images of these cracks, which are then analyzed using a machine learning algorithm by the server to detect and confirm the cracks and their severity.

Original languageEnglish
Title of host publication2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2023
PublisherIEEE Computer Society
Pages381-383
Number of pages3
ISBN (Electronic)9798350300529
DOIs
StatePublished - Sep 2023
Event20th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2023 - Madrid, Spain
Duration: 11 Sep 202314 Sep 2023

Publication series

NameAnnual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks workshops
Volume2023-September
ISSN (Print)2155-5486
ISSN (Electronic)2155-5494

Conference

Conference20th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2023
Country/TerritorySpain
CityMadrid
Period11/09/2314/09/23

Keywords

  • convolutional neural network
  • crack detection
  • pipelines
  • robots

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