Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution
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 principle...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/23/8133 |
| _version_ | 1797507117765099520 |
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| author | Clara I. Valero Enrique Ivancos Pla Rafael Vaño Eduardo Garro Fernando Boronat Carlos E. Palau |
| author_facet | Clara I. Valero Enrique Ivancos Pla Rafael Vaño Eduardo Garro Fernando Boronat Carlos E. Palau |
| author_sort | Clara I. Valero |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T04:44:04Z |
| format | Article |
| id | doaj.art-01e5a25e55414c3cb1b94161cfbd9f82 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T04:44:04Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-01e5a25e55414c3cb1b94161cfbd9f822023-11-23T03:04:28ZengMDPI AGSensors1424-82202021-12-012123813310.3390/s21238133Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management SolutionClara I. Valero0Enrique Ivancos Pla1Rafael Vaño2Eduardo Garro3Fernando Boronat4Carlos E. Palau5Communications Department, Universitat Politècnica de València, 46022 Valencia, SpainProdevelop S.L., 46003 Valencia, SpainCommunications Department, Universitat Politècnica de València, 46022 Valencia, SpainProdevelop S.L., 46003 Valencia, SpainCommunications Department, Universitat Politècnica de València, 46022 Valencia, SpainCommunications Department, Universitat Politècnica de València, 46022 Valencia, SpainCurrent 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.https://www.mdpi.com/1424-8220/21/23/8133maritime logisticsautomatic identification systemartificial intelligenceinternet of thingsartificial intelligence of things |
| spellingShingle | Clara I. Valero Enrique Ivancos Pla Rafael Vaño Eduardo Garro Fernando Boronat Carlos E. Palau Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution Sensors maritime logistics automatic identification system artificial intelligence internet of things artificial intelligence of things |
| title | Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution |
| title_full | Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution |
| title_fullStr | Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution |
| title_full_unstemmed | Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution |
| title_short | Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution |
| title_sort | design and development of an aiot architecture for introducing a vessel eta cognitive service in a legacy port management solution |
| topic | maritime logistics automatic identification system artificial intelligence internet of things artificial intelligence of things |
| url | https://www.mdpi.com/1424-8220/21/23/8133 |
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