Framework to support the Data Science of smart city models for decision-making oriented to the efficient dispatch of service petitions

The evolution of Smart Cities conveys continuous changes involving a great number of variables, which might hamper the development of evaluation tools and methodologies. Most of the metric models for Smart City are based on the selection of key performance indicators (KPI) according to the specific...

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Published in:IET software Vol. 14; no. 2; pp. 159 - 164
Main Authors: Estrada, Elsa, Maciel, Rocío, Negrón, Adriana Peña Pérez, López, Graciela Lara, Larios, Víctor, Ochoa, Alberto
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 01.04.2020
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ISSN:1751-8806, 1751-8814, 1751-8814
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Abstract The evolution of Smart Cities conveys continuous changes involving a great number of variables, which might hamper the development of evaluation tools and methodologies. Most of the metric models for Smart City are based on the selection of key performance indicators (KPI) according to the specific model objectives. As different organisations propose their own indicators generating different models, it is difficult to get a straightforward comparison among models. With the aim of dealing with this and other disadvantages, in this study, a framework based on the application of Data Science to the KPIs is proposed. This framework represents an infrastructure that goes through the treatment of Open Data, facilitating the evaluation of different models comparison intended for decision-making, and to the final stage of dispatching service reports. There are four components that integrate this framework (i) a tree structure to manage the KPIs; (ii) a designed JavaScript Object Notation document for service dispatch; (iii) Web applications for evaluations based on Smart People with four scenarios and; (iv) the infrastructure for reception and attention of reports.
AbstractList The evolution of Smart Cities conveys continuous changes involving a great number of variables, which might hamper the development of evaluation tools and methodologies. Most of the metric models for Smart City are based on the selection of key performance indicators (KPI) according to the specific model objectives. As different organisations propose their own indicators generating different models, it is difficult to get a straightforward comparison among models. With the aim of dealing with this and other disadvantages, in this study, a framework based on the application of Data Science to the KPIs is proposed. This framework represents an infrastructure that goes through the treatment of Open Data, facilitating the evaluation of different models comparison intended for decision-making, and to the final stage of dispatching service reports. There are four components that integrate this framework (i) a tree structure to manage the KPIs; (ii) a designed JavaScript Object Notation document for service dispatch; (iii) Web applications for evaluations based on Smart People with four scenarios and; (iv) the infrastructure for reception and attention of reports.
Author Negrón, Adriana Peña Pérez
López, Graciela Lara
Larios, Víctor
Ochoa, Alberto
Estrada, Elsa
Maciel, Rocío
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Issue 2
Keywords Java
key performance indicators
evaluation tools
Web applications
service dispatch
Open Data
Data Science
smart city models
service reports
public administration
metric models
decision-making
service petitions
JavaScript Object Notation document
decision making
smart cities
Smart People
Internet
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SubjectTerms Data Science
decision making
evaluation tools
Internet
Java
JavaScript Object Notation document
key performance indicators
metric models
Open Data
public administration
service dispatch
service petitions
service reports
smart cities
smart city models
Smart People
Special Issue: Software Engineering Applications to Solve Organisations Issues
Web applications
Title Framework to support the Data Science of smart city models for decision-making oriented to the efficient dispatch of service petitions
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