{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T13:02:17Z","timestamp":1775912537711,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001872","name":"Centre for Industrial Technological Development","doi-asserted-by":"publisher","award":["EXP 00110912\/INNO-20181033"],"award-info":[{"award-number":["EXP 00110912\/INNO-20181033"]}],"id":[{"id":"10.13039\/501100001872","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Current Internet of Things (IoT) stacks are frequently focused on handling an increasing volume of data that require a sophisticated interpretation through analytics to improve decision making and thus generate business value. In this paper, a cognitive IoT architecture based on FIWARE IoT principles is presented. The architecture incorporates a new cognitive component that enables the incorporation of intelligent services to the FIWARE framework, allowing to modernize IoT infrastructures with Artificial Intelligence (AI) technologies. This allows to extend the effective life of the legacy system, using existing assets and reducing costs. Using the architecture, a cognitive service capable of predicting with high accuracy the vessel port arrival is developed and integrated in a legacy sea traffic management solution. The cognitive service uses automatic identification system (AIS) and maritime oceanographic data to predict time of arrival of ships. The validation has been carried out using the port of Valencia. The results indicate that the incorporation of AI into the legacy system allows to predict the arrival time with higher accuracy, thus improving the efficiency of port operations. Moreover, the architecture is generic, allowing an easy integration of the cognitive services in other domains.<\/jats:p>","DOI":"10.3390\/s21238133","type":"journal-article","created":{"date-parts":[[2021,12,6]],"date-time":"2021-12-06T03:10:38Z","timestamp":1638760238000},"page":"8133","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7888-8394","authenticated-orcid":false,"given":"Clara I.","family":"Valero","sequence":"first","affiliation":[{"name":"Communications Department, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enrique","family":"Ivancos Pla","sequence":"additional","affiliation":[{"name":"Prodevelop S.L., 46003 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2372-6253","authenticated-orcid":false,"given":"Rafael","family":"Va\u00f1o","sequence":"additional","affiliation":[{"name":"Communications Department, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8160-0125","authenticated-orcid":false,"given":"Eduardo","family":"Garro","sequence":"additional","affiliation":[{"name":"Prodevelop S.L., 46003 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5525-3441","authenticated-orcid":false,"given":"Fernando","family":"Boronat","sequence":"additional","affiliation":[{"name":"Communications Department, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3795-5404","authenticated-orcid":false,"given":"Carlos E.","family":"Palau","sequence":"additional","affiliation":[{"name":"Communications Department, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,5]]},"reference":[{"key":"ref_1","unstructured":"United Nations (2021, November 29). Review of Maritime Transport. Available online: https:\/\/unctad.org\/system\/files\/official-document\/rmt2020_en.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1108\/09574090810872587","article-title":"Port centric logistics","volume":"19","author":"John","year":"2008","journal-title":"Int. J. Logist. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.oceaneng.2015.04.051","article-title":"Modelling of marine traffic flow complexity","volume":"104","author":"Wen","year":"2015","journal-title":"Ocean Eng."},{"key":"ref_4","first-page":"63","article-title":"Port community systems","volume":"3","author":"Long","year":"2009","journal-title":"World Cust. J."},{"key":"ref_5","first-page":"51","article-title":"How port community systems can contribute to port competitiveness: Developing a cost\u2013benefit framework","volume":"19","author":"Carlan","year":"2016","journal-title":"Res. Transp. Bus. Manag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/j.tra.2005.02.001","article-title":"Port privatization, efficiency and competitiveness: Some empirical evidence from container ports (terminals)","volume":"39","author":"Tongzon","year":"2005","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1080\/03088830902861086","article-title":"The terminalization of supply chains: Reassessing the role of terminals in port\/hinterland logistical relationships","volume":"36","author":"Rodrigue","year":"2009","journal-title":"Marit. Policy Manag."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1057\/mel.2008.18","article-title":"Operations research methods in maritime transport and freight logistics","volume":"11","author":"Sciomachen","year":"2009","journal-title":"Marit. Econ. Logist."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1057\/mel.2011.3","article-title":"Prediction of arrival times and human resources allocation for container terminal","volume":"13","author":"Fancello","year":"2011","journal-title":"Marit. Econ. Logist."},{"key":"ref_10","unstructured":"Jessen, H., and Werner, M.J. (2016). Directive 2002\/59\/EC establishing a Community vessel traffic monitoring and information system and repealing Council Directive 93\/75\/EEC. EU Maritime Transport Law, Nomos Verlagsgesellschaft mbH & Co. KG. [1st ed.]."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4015016","DOI":"10.1061\/(ASCE)WW.1943-5460.0000316","article-title":"Development of a vessel-performance forecasting system: Methodological framework and case study","volume":"142","author":"Camarero","year":"2016","journal-title":"J. Waterw. Port Coast. Ocean Eng."},{"key":"ref_12","unstructured":"Katsilieris, F., Braca, P., and Coraluppi, S. (2013, January 9\u201312). Detection of malicious AIS position spoofing by exploiting radar information. Proceedings of the 16th International Conference on Information Fusion, Istanbul, Turkey."},{"key":"ref_13","unstructured":"Baldauf, M., and Benedict, K. (2008, January 28). Aspects of Technical Reliability of Navigation Systems and Human Element in Case of Collision Avoidance. Proceedings of the Navigation Conference & Exhibition, London, UK."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"934","DOI":"10.32604\/iasc.2020.010125","article-title":"Wiener model identification using a modified brain storm optimization algorithm","volume":"26","author":"Pan","year":"2020","journal-title":"Intell. Autom. Soft Comput."},{"key":"ref_15","first-page":"335","article-title":"Identification and segmentation of impurities accumulated in a cold-trap device by using radiographic images","volume":"26","author":"Thamotharan","year":"2020","journal-title":"Intell. Autom. Soft Comput."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Pallotta, G., Vespe, M., and Bryan, K. (2013). Vessel Pattern Knowledge Discovery from AIS Data: A Framework for Anomaly Detection and Route Prediction. Entropy, 15.","DOI":"10.3390\/e15062218"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Mao, S., Tu, E., Zhang, G., Rachmawati, L., Rajabally, E., and Huang, G.-B. (2018). An Automatic Identification System (AIS) Database for Maritime Trajectory Prediction and Data Mining BT. Proceedings of ELM-2016, Springer.","DOI":"10.1007\/978-3-319-57421-9_20"},{"key":"ref_18","unstructured":"Meijer, R. (2017). Predicting the ETA of a Container Vessel Based on Route Identification Using AIS Data. [Master\u2019s Thesis, Delft University of Technology]."},{"key":"ref_19","unstructured":"Parolas, I. (2021, November 29). ETA Prediction for Containerships at the Port of Rotterdam Using Machine Learning Techniques. Available online: http:\/\/resolver.tudelft.nl\/uuid:9e95d11f-35ba-4a12-8b34-d137c0a4261d."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1109\/TITS.2017.2789279","article-title":"Estimated Time of Arrival Using Historical Vessel Tracking Data","volume":"20","author":"Alessandrini","year":"2019","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zijm, H., Klumpp, M., Clausen, U., and ten Hompel, M. (2016). Towards an Approach for Long Term AIS-Based Prediction of Vessel Arrival Times BT\u2014Logistics and Supply Chain Innovation: Bridging the Gap between Theory and Practice, Springer International Publishing.","DOI":"10.1007\/978-3-319-22288-2"},{"key":"ref_22","unstructured":"Pani, C., Vanelslander, T., Fancello, G., and Cannas, M. (2021, November 29). Prediction of Late\/Early Arrivals in Container Terminals\u2014A Qualitative Approach. Available online: https:\/\/iris.unica.it\/handle\/11584\/188788."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Bodunov, O., Schmidt, F., Martin, A., Brito, A., and Fetzer, C. (2018, January 25\u201329). Real-time destination and eta prediction for maritime traffic. Proceedings of the 12th ACM International Conference on Distributed and Event-Based Systems, Hamilton, New Zealand.","DOI":"10.1145\/3210284.3220502"},{"key":"ref_24","unstructured":"(2021, November 29). Watson Studio. Available online: https:\/\/www.ibm.com\/es-es\/cloud\/watson-studio\/faq."},{"key":"ref_25","unstructured":"Google AI (2021, November 29). Available online: https:\/\/ai.google\/tools\/."},{"key":"ref_26","unstructured":"(2021, November 29). Azure Machine Learning. Available online: https:\/\/azure.microsoft.com\/es-es\/services\/machine-learning\/."},{"key":"ref_27","unstructured":"(2021, November 29). Azure Cognitive Services. Available online: https:\/\/azure.microsoft.com\/es-es\/services\/cognitive-services\/."},{"key":"ref_28","unstructured":"Amazon AWS AI (2021, November 29). Available online: https:\/\/aws.amazon.com\/machine-learning\/."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Pramanik, P.K.D., Pal, S., and Choudhury, P. (2018). Beyond automation: The cognitive IoT. Artificial intelligence brings sense to the Internet of Things. Cognitive Computing for Big Data Systems over IoT, Springer.","DOI":"10.1007\/978-3-319-70688-7_1"},{"key":"ref_30","unstructured":"Robertson, J., and Robertson, S. (2021, November 29). Volere. Requirements Specification Templates. Available online: https:\/\/www.cs.uic.edu\/~i442\/VolereMaterials\/templateArchive16\/c%20Volere%20template16.pdf."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"45","DOI":"10.2753\/MIS0742-1222240302","article-title":"A design science research methodology for information systems research","volume":"24","author":"Peffers","year":"2007","journal-title":"J. Manag. Inf. Syst."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"75","DOI":"10.2307\/25148625","article-title":"Design science in information systems research","volume":"28","author":"Hevner","year":"2004","journal-title":"MIS Q."},{"key":"ref_33","unstructured":"(2021, November 29). Docker. Available online: https:\/\/www.docker.com."},{"key":"ref_34","unstructured":"(2021, November 29). World Weather Online. Available online: https:\/\/www.worldweatheronline.com\/developer\/api\/docs\/marine-weather-api.aspx."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1023\/A:1008363719778","article-title":"Incremental feature selection","volume":"9","author":"Liu","year":"1998","journal-title":"Appl. Intell."},{"key":"ref_36","unstructured":"(2021, November 29). Pickle. Available online: https:\/\/docs.python.org\/3\/library\/pickle.html."},{"key":"ref_37","unstructured":"(2021, November 29). Posidonia Operations. Available online: https:\/\/www.prodevelop.es\/puertos\/posidonia\/posidonia-operations."},{"key":"ref_38","unstructured":"(2021, November 29). PortEconomics. Available online: https:\/\/www.porteconomics.eu."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/23\/8133\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:39:57Z","timestamp":1760168397000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/23\/8133"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,5]]},"references-count":38,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["s21238133"],"URL":"https:\/\/doi.org\/10.3390\/s21238133","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,5]]}}}