Data-driven Leakage Monitoring
Data-Driven Leakage Monitoring is a systematic methodology for detecting and localizing water losses in distribution networks by analyzing empirical sensor and metering data through statistical, computational, or machine learning techniques to identify anomalous patterns indicative of leaks.
22
Publications
917
Citations
70
Authors
32
Institutions
Publications per year
2017–2026
17
Parents
22
Xi Wan, Parisa Khorsandi Kuhanestani, Raziyeh Farmani et al. · Journal of Water Resources Planning and Management · 2022 · 89 citations
Engineering, Civil Engineering, Water Resources Management +17
1–5 of 22
70
4
h-index
3
h-index
3
h-index
3
h-index
3
h-index
1–5 of 70
32
Institut de Robòtica i Informàtica Industrial
Barcelona, Spain
4 h-index
11 publications
706 citations
Universitat Politècnica de Catalunya
Barcelona, Spain
4 h-index
12 publications
734 citations
Los Alamos National Laboratory
Los Alamos, United States
2 h-index
10 publications
510 citations
PetroChina Southwest Oil and Gas Field Company (China)
Chengdu, China
2 h-index
2 publications
55 citations
Université de Lille
Lille, France
2 h-index
4 publications
193 citations

École des Mines de Douai
Douai, France
2 h-index
4 publications
289 citations

Chongqing University
Chongqing, China
2 h-index
2 publications
55 citations

University of Naples Federico II
Naples, Italy
1 h-index
1 publications
27 citations
1–8 of 32
3 publications · 77 citations
3
h-index
2 publications · 116 citations
2
h-index
2 publications · 102 citations
2
h-index
2 publications · 61 citations
2
h-index
1 publications · 20 citations
1
h-index
1–5