2024-03-29T04:34:23Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/72362023-03-17T11:23:39Zcom_10259_3847com_10259_5086com_10259_2604col_10259_3848
Deepint.net: A Rapid Deployment Platform for Smart Territories
Corchado, Juan M.
Chamoso, Pablo
Hernández González, Guillermo
San Román Gutiérrez, Agustín
Rivas Camacho, Alberto
González Briones, Alfonso
Pinto Santos, Francisco
Goyenechea, Enrique
García Retuerta, David
Alonso Miguel, María
Bellido Hernández, Beatriz
Valdeolmillos Villaverde, Diego
Sánchez Verdejo, Manuel
Plaza Martínez, Pablo
López Pérez, Manuel
Manzano García, Sergio
Alonso Rincón, Ricardo S.
Casado Vara, Roberto Carlos
Prieto Tejedor, Javier
Prieta, Fernando de la
Rodríguez González, Sara
Parra Domínguez, Javier
Saberi Mohamad, Mohd
Trabelsi, Saber
Díaz Plaza, Enrique
García Coria, José Alberto
Yigitcanlar, Tan
Novais, Paulo
Omatu, Sigeru
Smart cities
Smart cyberphysical platform
Data analysis
Data visualization
Edge computing
Artificial intelligence
Bike renting
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 multifunctional 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.
2023-01-13T10:09:31Z
2023-01-13T10:09:31Z
2023-01-13T10:09:31Z
2021-01
info:eu-repo/semantics/article
http://hdl.handle.net/10259/7236
10.3390/s21010236
1424-8220
eng
Sensors. 2021, V. 21, n. 1, e236
https://doi.org/10.3390/s21010236
info:eu-repo/grantAgreement/EC/H2020/777630/EU/Multi-scale Observation and Monitoring of railway Infrastructure Threats/
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/
info:eu-repo/grantAgreement/CYTED//518RT0558//CIUDADES INTELIGENTES TOTALMENTE INTEGRALES, EFICIENTES Y SOSTENIBLES (CITIES)/
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
Atribución 4.0 Internacional
MDPI