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<dc:title>Deepint.net: A Rapid Deployment Platform for Smart Territories</dc:title>
<dc:creator>Corchado, Juan M.</dc:creator>
<dc:creator>Chamoso, Pablo</dc:creator>
<dc:creator>Hernández González, Guillermo</dc:creator>
<dc:creator>San Román Gutiérrez, Agustín</dc:creator>
<dc:creator>Rivas Camacho, Alberto</dc:creator>
<dc:creator>González Briones, Alfonso</dc:creator>
<dc:creator>Pinto Santos, Francisco</dc:creator>
<dc:creator>Goyenechea, Enrique</dc:creator>
<dc:creator>García Retuerta, David</dc:creator>
<dc:creator>Alonso Miguel, María</dc:creator>
<dc:creator>Bellido Hernández, Beatriz</dc:creator>
<dc:creator>Valdeolmillos Villaverde, Diego</dc:creator>
<dc:creator>Sánchez Verdejo, Manuel</dc:creator>
<dc:creator>Plaza Martínez, Pablo</dc:creator>
<dc:creator>López Pérez, Manuel</dc:creator>
<dc:creator>Manzano García, Sergio</dc:creator>
<dc:creator>Alonso Rincón, Ricardo S.</dc:creator>
<dc:creator>Casado Vara, Roberto Carlos</dc:creator>
<dc:creator>Prieto Tejedor, Javier</dc:creator>
<dc:creator>Prieta, Fernando de la</dc:creator>
<dc:creator>Rodríguez González, Sara</dc:creator>
<dc:creator>Parra Domínguez, Javier</dc:creator>
<dc:creator>Saberi Mohamad, Mohd</dc:creator>
<dc:creator>Trabelsi, Saber</dc:creator>
<dc:creator>Díaz Plaza, Enrique</dc:creator>
<dc:creator>García Coria, José Alberto</dc:creator>
<dc:creator>Yigitcanlar, Tan</dc:creator>
<dc:creator>Novais, Paulo</dc:creator>
<dc:creator>Omatu, Sigeru</dc:creator>
<dc:subject>Smart cities</dc:subject>
<dc:subject>Smart cyberphysical platform</dc:subject>
<dc:subject>Data analysis</dc:subject>
<dc:subject>Data visualization</dc:subject>
<dc:subject>Edge computing</dc:subject>
<dc:subject>Artificial intelligence</dc:subject>
<dc:subject>Bike renting</dc:subject>
<dc:subject>Informática</dc:subject>
<dc:subject>Computer science</dc:subject>
<dc:description>This paper presents an efficient cyberphysical platform for the smart management of&#xd;
smart territories. It is efficient because it facilitates the implementation of data acquisition and&#xd;
data management methods, as well as data representation and dashboard configuration. The&#xd;
platform allows for the use of any type of data source, ranging from the measurements of a multifunctional IoT sensing devices to relational and non-relational databases. It is also smart because&#xd;
it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for&#xd;
data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with&#xd;
the edge computing concept, allowing for the distribution of intelligence and the use of intelligent&#xd;
sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create&#xd;
intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to&#xd;
the previous approach of managing an entire megacity. In this paper, the platform is presented,&#xd;
and its architecture and functionalities are described. Moreover, its operation has been validated&#xd;
in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This&#xd;
platform could enable smart territories to develop adapted knowledge management systems, adapt&#xd;
them to new requirements and to use multiple types of data, and execute efficient computational&#xd;
and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts&#xd;
through explainable artificial intelligence models that obtain data from IoT sensors, databases, the&#xd;
Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data&#xd;
processing techniques.</dc:description>
<dc:description>This work has been partially supported by the European Regional Development Fund (ERDF) through the Interreg Spain-Portugal V-A Program (POCTEP) under grant 0677_DISRUPTIVE_2_E, the project My-TRAC: My TRAvel Companion (H2020-S2RJU-2017), the project LAPASSION, CITIES (CYTED 518RT0558) and the company DCSC. Pablo Chamoso’s research work has been funded through the Santander Iberoamerican Research Grants, call 2020/2021, under the direction of Paulo Novais.</dc:description>
<dc:date>2023-01-13T10:09:31Z</dc:date>
<dc:date>2023-01-13T10:09:31Z</dc:date>
<dc:date>2021-01</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:identifier>http://hdl.handle.net/10259/7236</dc:identifier>
<dc:identifier>10.3390/s21010236</dc:identifier>
<dc:identifier>1424-8220</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Sensors. 2021, V. 21, n. 1, e236</dc:relation>
<dc:relation>https://doi.org/10.3390/s21010236</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/EC/H2020/777630/EU/Multi-scale Observation and Monitoring of railway Infrastructure Threats/</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/EC/POCTEP/0677_DISRUPTIVE_2_E/EU/Intensifying the activity of Digital Innovation Hubs within the PocTep region to boost the development of disruptive and last generation ICTs through cross-border cooperation/</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/CYTED//518RT0558//CIUDADES INTELIGENTES TOTALMENTE INTEGRALES, EFICIENTES Y SOSTENIBLES (CITIES)/</dc:relation>
<dc:rights>Atribución 4.0 Internacional</dc:rights>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:format>application/pdf</dc:format>
<dc:publisher>MDPI</dc:publisher>
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