A smart sewer asset information model to enable an ‘Internet of Things’ for operational wastewater management

Vikki Edmondson, Martin Cerny, Michael Lim, Barry Gledson, Steven Lockley, John Woodward

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)
83 Downloads (Pure)

Abstract

Real-time prediction of flooding is vital for the successful future operational management of the UK sewerage network. Recent advances in smart infrastructure and the emergence of the Internet of Things (IoT), presents an opportunity within the wastewater sector to harness and report in real-time sewer condition data for operation management. This study presents the design and development of a prototype Smart Sewer Asset Information Model (SSAIM) for an existing sewerage network. The SSAIM, developed using Industry Foundation Class version 4 (IFC4) an open neutral data format for BIM, incorporates distributed smart sensors to enable real-time monitoring and reporting of sewer asset performance. Results describe an approach for sensor data analysis to facilitate the real-time prediction of flooding.
Original languageEnglish
Pages (from-to)193-205
JournalAutomation in Construction
Volume91
Early online date18 Mar 2018
DOIs
Publication statusPublished - 1 Jul 2018

Fingerprint

Dive into the research topics of 'A smart sewer asset information model to enable an ‘Internet of Things’ for operational wastewater management'. Together they form a unique fingerprint.

Cite this