{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T04:06:39Z","timestamp":1784693199484,"version":"3.55.0"},"reference-count":46,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T00:00:00Z","timestamp":1753142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"US Department of Energy\u2019s Industrial Technologies Office (ITO)","award":["DE-AC05\u201300OR22725"],"award-info":[{"award-number":["DE-AC05\u201300OR22725"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Smart Cities"],"abstract":"<jats:p>The aging water distribution system in the United States, constructed mainly during the 1970s with some pipes dating back 125 years, is experiencing significant deterioration leading to substantial water losses. Along with the potential for water loss savings, improvements in the distribution system by using leak detection technologies can create net energy and cost savings. In this work, a new framework has been presented to calculate the economic level of leakage within water supply and distribution systems for two primary leak detection technologies (acoustic vs. satellite). In this work, a new framework is presented to calculate the economic level of leakage (ELL) within water supply and distribution systems to support smart infrastructure in smart cities. A case study focused using water audit data from Atlanta, Georgia, compared the costs of two leak mitigation technologies: conventional acoustic leak detection and artificial intelligence\u2013assisted satellite leak detection technology, which employs machine learning algorithms to identify potential leak signatures from satellite imagery. The ELL results revealed that conducting one survey would be optimum for an acoustic survey, whereas the method suggested that it would be expensive to utilize satellite-based leak detection technology. However, results for cumulative financial analysis over a 3-year period for both technologies revealed both to be economically favorable with conventional acoustic leak detection technology generating higher net economic benefits of USD 2.4 million, surpassing satellite detection by 50%. A broader national analysis was conducted to explore the potential benefits of US water infrastructure mirroring the exemplary conditions of Germany and The Netherlands. Achieving similar infrastructure leakage index (ILI) values could result in annual cost savings of $4\u2013$4.8 billion and primary energy savings of 1.6\u20131.9 TWh. These results demonstrate the value of combining economic modeling with advanced leak detection technologies to support sustainable, cost-efficient water infrastructure strategies in urban environments, contributing to more sustainable smart living outcomes.<\/jats:p>","DOI":"10.3390\/smartcities8040122","type":"journal-article","created":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T13:35:28Z","timestamp":1753191328000},"page":"122","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Evaluating Acoustic vs. AI-Based Satellite Leak Detection in Aging US Water Infrastructure: A Cost and Energy Savings Analysis"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8540-6717","authenticated-orcid":false,"given":"Prashant","family":"Nagapurkar","sequence":"first","affiliation":[{"name":"Manufacturing Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7552-5854","authenticated-orcid":false,"given":"Naushita","family":"Sharma","sequence":"additional","affiliation":[{"name":"Manufacturing Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susana","family":"Garcia","sequence":"additional","affiliation":[{"name":"Building Technology & Urban Systems Division, Lawrence Berkeley National Laboratory, Berkeley, CA 97420, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sachin","family":"Nimbalkar","sequence":"additional","affiliation":[{"name":"Manufacturing Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,22]]},"reference":[{"key":"ref_1","unstructured":"American Society of Civil Engineers (ASCE) (2024, January 03). 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