CrowDSL: Platform for Incidents Management in a Smart City Context

Autor: Cristian González García, Vicente García-Díaz, Darío Rodríguez-García
Rok vydání: 2021
Předmět:
Zdroj: Big Data and Cognitive Computing
Volume 5
Issue 3
Big Data and Cognitive Computing, Vol 5, Iss 44, p 44 (2021)
Scopus
RUO. Repositorio Institucional de la Universidad de Oviedo
instname
ISSN: 2504-2289
DOI: 10.3390/bdcc5030044
Popis: The final objective of smart cities is to optimize services and improve the quality of life of their citizens, who can play important roles due to the information they can provide. This information can be used in order to enhance many sectors involved in city activity such as transport, energy or health. Crowd-sourcing initiatives focus their efforts on making cities safer places that are adapted to the population size they host. In this way, citizens are able to report the issues they identify to the relevant body so that they can be fixed and, at the same time, they can provide useful information to other citizens. There are several projects aimed at reporting incidents in a smart city context. In this paper, we propose the use of model-driven engineering by designing a graphical domain-specific language to abstract and improve the incident-reporting process. With the use of a domain-specific language, we can obtain several benefits in our research for users and cities. For instance, we can shorten the time for reporting the events by users and, at the same time, we gain an expressive power compared to other methodologies for incident reporting. In addition, it can be reused and is centered in this specific domain after being studied. Furthermore, we have evaluated the DSL with different users, obtaining a high satisfaction percentage.
Databáze: OpenAIRE