{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T03:18:11Z","timestamp":1758079091890,"version":"3.44.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686196","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,16]]},"abstract":"<jats:p>Climate change is among the most urgent challenges of our era, and maritime transport represents a significant source of GreenHouse-Gas and pollutant emissions despite its relative efficiency. To drive both operational and environmental sustainability, a unified, data-driven framework for evaluating ship Berthing Manoeuvre (BM) is presented. The aim of this work is to provide a decision-support system for comprehensive BM evaluation. A structured set of economic, operational, and environmental KPIs is assessed, and both CRITIC and Entropy methods are applied to determine their weights, yielding a single Berthing Efficiency Index (BEI). A modular Python implementation collects IoT and onboard sensor data, cleans and segments maneuvers, computes KPIs, detects anomalies, and presents findings via an interactive dashboard. Validation employed datasets from twin vessels\u2014one performing conventional manual berthing and the other assisted by automated systems. Clustering analysis revealed distinct performance profiles, while BEI aggregation demonstrated the automated system\u2019s superior efficiency: lower CO2 emissions and reduced fuel consumption. Cross-fleet benchmarking further confirmed the framework accuracy, reusability, and scalability across diverse operational scenarios. By identifying inefficiencies and delivering evidence-based insights, this approach facilitates optimized berthing practices, targeted crew training, and informed technology adoption, thereby contributing to smarter, greener, and more resilient maritime operations.<\/jats:p>","DOI":"10.3233\/faia250529","type":"book-chapter","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T13:19:31Z","timestamp":1758028771000},"source":"Crossref","is-referenced-by-count":0,"title":["A Data-Driven Framework for the Evaluation of Autonomous and Traditional Berthing Maneuvers in Maritime Operations"],"prefix":"10.3233","author":[{"given":"Giuseppe","family":"Franzese","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3175-273X","authenticated-orcid":false,"given":"Luisa","family":"Montella","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, Piazzale V. Tecchio 80, Naples, 80125, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2007-5598","authenticated-orcid":false,"given":"Teresa","family":"Murino","sequence":"additional","affiliation":[{"name":"Department of Chemical, Materials and Industrial Engineering, University of Naples Federico II, P.le Tecchio 80, Napoli, 80125, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9114-5234","authenticated-orcid":false,"given":"Andrea","family":"Somma","sequence":"additional","affiliation":[{"name":"Department of Chemical, Materials and Industrial Engineering, University of Naples Federico II, P.le Tecchio 80, Napoli, 80125, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Monica","family":"Strazzullo","sequence":"additional","affiliation":[{"name":"Grimaldi Group, Via Marchese Campodisola, 13, Napoli, 80133, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","New Trends in Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250529","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T13:19:31Z","timestamp":1758028771000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250529"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,16]]},"ISBN":["9781643686196"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250529","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,16]]}}}