Evidence map›Paper›PMID 33401468›Full record

ArticleSensors (Basel, Switzerland)2021

Deepint.net: A Rapid Deployment Platform for Smart Territories.

Juan M Corchado, Pablo Chamoso, Guillermo Hernández, Agustín San Roman Gutierrez, Alberto Rivas Camacho, Alfonso González-Briones, Francisco Pinto-Santos, Enrique Goyenechea, David Garcia-Retuerta, María Alonso-Miguel and 19 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

29 authors.

Juan M CorchadoBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0002-2829-1829
Pablo ChamosoBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0001-5109-3583
Guillermo HernándezAir Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain.ORCID 0000-0002-7481-5961
Agustín San Roman GutierrezAir Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain.
Alberto Rivas CamachoBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0002-9558-9895
Alfonso González-BrionesResearch Group on Agent-Based, Social and Interdisciplinary Applications (GRASIA), Complutense University of Madrid, 28040 Madrid, Spain.ORCID 0000-0002-3444-4393
Francisco Pinto-SantosBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0002-9500-9336
Enrique GoyenecheaBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.
David Garcia-RetuertaBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0003-2351-068X
María Alonso-MiguelBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.
Beatriz Bellido HernandezBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.
Diego Valdeolmillos VillaverdeBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.
Manuel Sanchez-VerdejoAir Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain.
Pablo Plaza-MartínezBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.
Manuel López-PérezBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.
Sergio Manzano-GarcíaBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0002-7768-3124
Ricardo S AlonsoAir Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain.ORCID 0000-0002-6599-0186
Roberto Casado-VaraBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0003-0198-696X
Javier Prieto TejedorBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0001-8175-2201
Fernando de la PrietaBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0002-8239-5020
Sara Rodríguez-GonzálezBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.
Javier Parra-DomínguezBISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.ORCID 0000-0002-1088-9152
Mohd Saberi MohamadInstitute For Artificial Intelligence & Big Data, Universiti Malaysia Kelantan, Kelantan 16100, Malaysia.ORCID 0000-0002-1079-4559
Saber TrabelsiTexas A&M University at Qatar, Doha 23874, Qatar.
Enrique Díaz-PlazaIBM, 28108 Madrid, Spain.
Jose Alberto Garcia-CoriaViewnext, 28036 Madrid, Spain.
Tan YigitcanlarSchool of Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia.ORCID 0000-0001-7262-7118
Paulo NovaisALGORITMI Centre/Department of Informatics, University of Minho, 4710-070 Braga, Portugal.
Sigeru OmatuDigital Manufacturing Education and Research Center, Division of Data Driven Smart System, Hiroshima University, Hiroshima 739-8511, Japan.

Funding

European Regional Development Fund 0677_DISRUPTIVE_2_E
6 · The paper itself

Abstract

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.

Indexed as

artificial intelligencebike rentingdata analysisdata visualizationedge computingsmart citiessmart cyberphysical platform

Identifiers

PMID33401468
PMCPMC7795292

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.