iOLE—Human-Centered Software Design for Leakage Detection in Water Distribution Networks

Leakages in water distribution networks still pose major challenges to water utilities. Despite numerous technological advances, the adoption of digital leakage detection technology remains a slow process. Here, we present the project iOLE—intelligent Online LEakage detection, where we aim to increase the applicability of automated leak detection in practice through enhanced user experience and detection robustness. iOLE employs a human-centered design approach that involves the feedback of potential users during its development process to maximize subsequent user acceptance. To this end, we design a graphical user interface, combine model-based and data-driven leakage detection, and conduct a comprehensive robustness analysis.

Authors

Institutions

Publication Details

Published
2024-11-20
DOI
https://doi.org/10.3390/engproc2024069207
Primary Topic
Water Systems and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

iOLE—Human-Centered Software Design for Leakage Detection in Water Distribution Networks

David Steffelbauer, Ivo Daniel, Andrea Cominola, Bernd Lindemann et al.
Water Systems and Optimization
article

iOLE—Human-Centered Software Design for Leakage Detection in Water Distribution Networks

David Steffelbauer, Ivo Daniel, Andrea Cominola, Bernd Lindemann, Ella Steins, Johannes Koslowski, Enrique Campbell, Jonas Schorr, Sophie Persigehl, Jens Kley-Holsteg
article en

Abstract

Leakages in water distribution networks still pose major challenges to water utilities. Despite numerous technological advances, the adoption of digital leakage detection technology remains a slow process. Here, we present the project iOLE—intelligent Online LEakage detection, where we aim to increase the applicability of automated leak detection in practice through enhanced user experience and detection robustness. iOLE employs a human-centered design approach that involves the feedback of potential users during its development process to maximize subsequent user acceptance. To this end, we design a graphical user interface, combine model-based and data-driven leakage detection, and conduct a comprehensive robustness analysis.

Einstein Center Digital Future (DE), Berlin Centre of Competence for Water (DE), Technische Universität Berlin (DE)
Clean water and sanitation
Openalex Percentile: Top 76%
Water Systems and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

iOLE—Human-Centered Software Design for Leakage Detection in Water Distribution Networks — David Steffelbauer, Ivo Daniel, et al. · (2024) | TGRS Research Map | TGRS