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<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:date>2021-01</dc:date>
<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>
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<dc:identifier>http://hdl.handle.net/10259/7236</dc:identifier>
<dc:language>eng</dc:language>
<dc:publisher>MDPI</dc:publisher>
<dc:title>Deepint.net: A Rapid Deployment Platform for Smart Territories</dc:title>
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