{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T07:43:26Z","timestamp":1770191006764,"version":"3.49.0"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032141064","type":"print"},{"value":"9783032141071","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-14107-1_32","type":"book-chapter","created":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T19:37:00Z","timestamp":1770147420000},"page":"382-396","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integration of\u00a0Multi-source Data for\u00a0Wastewater Network Management"],"prefix":"10.1007","author":[{"given":"Neda","family":"Mashhadi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Salem","family":"Benferhat","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,2,4]]},"reference":[{"key":"32_CR1","unstructured":"American Society of Civil Engineers. report card for america\u2019s infrastructure: Wastewater (2021)"},{"key":"32_CR2","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/B978-0-12-394432-0.00004-4","volume-title":"Subsea Pipeline Integrity and Risk Management","author":"Y Bai","year":"2014","unstructured":"Bai, Y., Bai, Q.: Chapter 4 - pipeline inspection and subsea repair. In: Bai, Y., Bai, Q. (eds.) Subsea Pipeline Integrity and Risk Management, pp. 73\u201399. Gulf Professional Publishing, Boston (2014)"},{"key":"32_CR3","doi-asserted-by":"crossref","unstructured":"Biswas, R., Mutz, M., Pimplikar, P., Ahmed, N., Werth, D.: Sewer-AI: sustainable automated analysis of real-world sewer videos using DNNs. In: International Conference on Pattern Recognition Applications and Methods (2023)","DOI":"10.5220\/0011709400003411"},{"key":"32_CR4","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.compind.2018.03.020","volume":"99","author":"LM Dang","year":"2018","unstructured":"Dang, L.M., Hassan, S.I., Im, S., Mehmood, I., Moon, H.: Utilizing text recognition for the defects extraction in sewers cctv inspection videos. Comput. Ind. 99, 96\u2013109 (2018)","journal-title":"Comput. Ind."},{"key":"32_CR5","unstructured":"Esri. Bearing distance to line (data management toolbox) \u2014 arcgis desktop. https:\/\/desktop.arcgis.com\/en\/arcmap\/latest\/tools\/data-management-toolbox\/bearing-distance-to-line.html (2021). Accessed 20 July 2025"},{"key":"32_CR6","unstructured":"GeoPy Contributors. Geopy documentation. https:\/\/geopy.readthedocs.io\/, 2006\u20132018. Accessed 20 July 2025"},{"key":"32_CR7","doi-asserted-by":"crossref","unstructured":"Guo, W., Soibelman, L., Garrett, J.H.: Automated defect detection in urban wastewater pipes using invariant features found in video images. In: Computing in Civil Engineering (2009), pp. 1194\u20131203 (2009)","DOI":"10.1061\/41020(339)121"},{"key":"32_CR8","doi-asserted-by":"publisher","first-page":"04013014","DOI":"10.1061\/(ASCE)IS.1943-555X.0000161","volume":"20","author":"MR Halfawy","year":"2014","unstructured":"Halfawy, M.R., Hengmeechai, J.: Efficient algorithm for crack detection in sewer images from closed-circuit television inspections. J. Infrastr. Syst. 20, 04013014 (2014)","journal-title":"J. Infrastr. Syst."},{"key":"32_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2019.103061","volume":"111","author":"JB Haurum","year":"2020","unstructured":"Haurum, J.B., Moeslund, T.B.: A survey on image-based automation of cctv and sset sewer inspections. Autom. Constr. 111, 103061 (2020)","journal-title":"Autom. Constr."},{"key":"32_CR10","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1111\/j.1467-8667.2006.00445.x","volume":"21","author":"S Iyer","year":"2006","unstructured":"Iyer, S., Sinha, S.K.: Segmentation of pipe images for crack detection in buried sewers. Comput. Aided Civil Infrastr. Eng. 21, 395\u2013410 (2006)","journal-title":"Comput. Aided Civil Infrastr. Eng."},{"key":"32_CR11","doi-asserted-by":"publisher","first-page":"04019047","DOI":"10.1061\/(ASCE)CP.1943-5487.0000866","volume":"34","author":"SS Kumar","year":"2020","unstructured":"Kumar, S.S., Wang, M., Abraham, D.M., Jahanshahi, M.R., Iseley, T., Cheng, J.C.: Deep learning-based automated detection of sewer defects in cctv videos. J. Comput. Civ. Eng. 34, 04019047 (2020)","journal-title":"J. Comput. Civ. Eng."},{"key":"32_CR12","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/B978-0-12-813578-5.00002-0","volume-title":"Reliability and Maintainability of In-Service Pipelines","author":"M Mahmoodian","year":"2018","unstructured":"Mahmoodian, M.: Chapter 2 - pipeline inspection and maintenance. In: Mahmoodian, M. (ed.) Reliability and Maintainability of In-Service Pipelines, pp. 49\u201378. Gulf Professional Publishing (2018)"},{"key":"32_CR13","unstructured":"Molines, N., Siret, D., Musy, M., Groleau, D.: In: Benefits and limits of GIS for managing heterogeneous environmental data in sustainable urban design: example of the adequa project. In: In Proceedings of the 9th AGILE International Conference on Geographic Information Scienc, pp. 255\u2013262. Visegr\u00e1d, Hungary (2006)"},{"issue":"3","key":"32_CR14","doi-asserted-by":"publisher","first-page":"04020018","DOI":"10.1061\/(ASCE)IS.1943-555X.0000553","volume":"26","author":"S Moradi","year":"2020","unstructured":"Moradi, S., Zayed, T., Nasiri, F., Golkhoo, F.: Automated anomaly detection and localization in sewer inspection videos using proportional data modeling and deep learning\u2013based text recognition. J. Infrastr. Syst. 26(3), 04020018 (2020)","journal-title":"J. Infrastr. Syst."},{"key":"32_CR15","doi-asserted-by":"crossref","unstructured":"Patel, J., Sinha, S.K.: Geographic information system (GIS) web-based water pipeline data visualization for decision support. In: Pipelines 2019, pp. 95\u2013103. American Society of Civil Engineers Reston (2019)","DOI":"10.1061\/9780784482506.010"},{"key":"32_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.envsoft.2021.105279","volume":"148","author":"K Zhang","year":"2021","unstructured":"Zhang, K., Shalehy, M.H., Ezaz, G.T., Chakraborty, A., Mohib, K., Liu, L.: An integrated flood risk assessment approach based on coupled hydrological-hydraulic modeling and bottom-up hazard vulnerability analysis. Environ. Model. Softw. 148, 105279 (2021)","journal-title":"Environ. Model. Softw."},{"key":"32_CR17","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1007\/978-981-97-9613-7_14","volume-title":"Intelligent Systems and Data Science","author":"MT Tran-Nguyen","year":"2025","unstructured":"Tran-Nguyen, M.T., Benferhat, S., Chahinian, N., Delenne, C., Do, T.N.: Building a wastewater network graph from inspection videos. In: Benferhat, S., Tran-Nguyen, M.T., Do, T.N. (eds.) Intelligent Systems and Data Science, pp. 188\u2013202. Springer, Singapore (2025)"},{"key":"32_CR18","first-page":"14","volume":"R208","author":"M Uzair","year":"2002","unstructured":"Uzair, M., Shamsi, S.: Gis applications in inspection and maintenance of collection systems. J. Water Manag. Modeling R208, 14\u20131 (2002)","journal-title":"J. Water Manag. Modeling"},{"key":"32_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2020.103438","volume":"121","author":"M Wang","year":"2021","unstructured":"Wang, M., Kumar, S.S., Cheng, J.C.: Automated sewer pipe defect tracking in cctv videos based on defect detection and metric learning. Automation Constr. 121, 103438 (2021)","journal-title":"Automation Constr."},{"key":"32_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2021.103622","volume":"125","author":"X Yin","year":"2021","unstructured":"Yin, X., Ma, T., Bouferguene, A., Al-Hussein, M.: Automation for sewer pipe assessment: Cctv video interpretation algorithm and sewer pipe video assessment (spva) system development. Automation Constr. 125, 103622 (2021)","journal-title":"Automation Constr."},{"key":"32_CR21","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.resconrec.2009.07.001","volume":"54","author":"M Zamorano","year":"2009","unstructured":"Zamorano, M., Molero, E., Grindlay, A., Rodr\u00edguez, M.L., Hurtado, A., Calvo, F.J.: A planning scenario for the application of geographical information systems in municipal waste collection. a case of churriana de la vega (granada, spain). Res. Conservation Recycling 54, 123\u2013133 (2009)","journal-title":"Res. Conservation Recycling"}],"container-title":["Lecture Notes in Computer Science","Social Networks Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-14107-1_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T19:37:03Z","timestamp":1770147423000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-14107-1_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032141064","9783032141071"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-14107-1_32","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"4 February 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ASONAM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advances in Social Networks Analysis and Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":", ON","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"asonam-12025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/asonam.cpsc.ucalgary.ca\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}