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author Corchado, Juan M.
Chamoso, Pablo
Hernández, Guillermo
Gutierrez, Agustín San Roman
Camacho, Alberto Rivas
González-Briones, Alfonso
Pinto-Santos, Francisco
Goyenechea, Enrique
Garcia-Retuerta, David
Alonso-Miguel, María
Hernandez, Beatriz Bellido
Villaverde, Diego Valdeolmillos
Sanchez-Verdejo, Manuel
Plaza-Martínez, Pablo
López-Pérez, Manuel
Manzano-García, Sergio
Alonso, Ricardo S.
Casado-Vara, Roberto
Tejedor, Javier Prieto
de la Prieta, Fernando
Rodríguez-González, Sara
Parra-Domínguez, Javier
Mohamad, Mohd Saberi
Trabelsi, Saber
Díaz-Plaza, Enrique
Garcia-Coria, Jose Alberto
Yigitcanlar, Tan
Novais, Paulo
Omatu, Sigeru
author_facet Corchado, Juan M.
Chamoso, Pablo
Hernández, Guillermo
Gutierrez, Agustín San Roman
Camacho, Alberto Rivas
González-Briones, Alfonso
Pinto-Santos, Francisco
Goyenechea, Enrique
Garcia-Retuerta, David
Alonso-Miguel, María
Hernandez, Beatriz Bellido
Villaverde, Diego Valdeolmillos
Sanchez-Verdejo, Manuel
Plaza-Martínez, Pablo
López-Pérez, Manuel
Manzano-García, Sergio
Alonso, Ricardo S.
Casado-Vara, Roberto
Tejedor, Javier Prieto
de la Prieta, Fernando
Rodríguez-González, Sara
Parra-Domínguez, Javier
Mohamad, Mohd Saberi
Trabelsi, Saber
Díaz-Plaza, Enrique
Garcia-Coria, Jose Alberto
Yigitcanlar, Tan
Novais, Paulo
Omatu, Sigeru
author_sort Corchado, Juan M.
collection PubMed
description This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the 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 processing techniques.
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spelling pubmed-77952922021-01-10 Deepint.net: A Rapid Deployment Platform for Smart Territories Corchado, Juan M. Chamoso, Pablo Hernández, Guillermo Gutierrez, Agustín San Roman Camacho, Alberto Rivas González-Briones, Alfonso Pinto-Santos, Francisco Goyenechea, Enrique Garcia-Retuerta, David Alonso-Miguel, María Hernandez, Beatriz Bellido Villaverde, Diego Valdeolmillos Sanchez-Verdejo, Manuel Plaza-Martínez, Pablo López-Pérez, Manuel Manzano-García, Sergio Alonso, Ricardo S. Casado-Vara, Roberto Tejedor, Javier Prieto de la Prieta, Fernando Rodríguez-González, Sara Parra-Domínguez, Javier Mohamad, Mohd Saberi Trabelsi, Saber Díaz-Plaza, Enrique Garcia-Coria, Jose Alberto Yigitcanlar, Tan Novais, Paulo Omatu, Sigeru Sensors (Basel) Article This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the 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 processing techniques. MDPI 2021-01-01 /pmc/articles/PMC7795292/ /pubmed/33401468 http://dx.doi.org/10.3390/s21010236 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Corchado, Juan M.
Chamoso, Pablo
Hernández, Guillermo
Gutierrez, Agustín San Roman
Camacho, Alberto Rivas
González-Briones, Alfonso
Pinto-Santos, Francisco
Goyenechea, Enrique
Garcia-Retuerta, David
Alonso-Miguel, María
Hernandez, Beatriz Bellido
Villaverde, Diego Valdeolmillos
Sanchez-Verdejo, Manuel
Plaza-Martínez, Pablo
López-Pérez, Manuel
Manzano-García, Sergio
Alonso, Ricardo S.
Casado-Vara, Roberto
Tejedor, Javier Prieto
de la Prieta, Fernando
Rodríguez-González, Sara
Parra-Domínguez, Javier
Mohamad, Mohd Saberi
Trabelsi, Saber
Díaz-Plaza, Enrique
Garcia-Coria, Jose Alberto
Yigitcanlar, Tan
Novais, Paulo
Omatu, Sigeru
Deepint.net: A Rapid Deployment Platform for Smart Territories
title Deepint.net: A Rapid Deployment Platform for Smart Territories
title_full Deepint.net: A Rapid Deployment Platform for Smart Territories
title_fullStr Deepint.net: A Rapid Deployment Platform for Smart Territories
title_full_unstemmed Deepint.net: A Rapid Deployment Platform for Smart Territories
title_short Deepint.net: A Rapid Deployment Platform for Smart Territories
title_sort deepint.net: a rapid deployment platform for smart territories
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795292/
https://www.ncbi.nlm.nih.gov/pubmed/33401468
http://dx.doi.org/10.3390/s21010236
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