LGeoSIM: um modelo semântico de dados para cidades inteligentes

Abstract

Smart cities involve a myriad of interconnected systems designed to promote better management of urban and natural resources in cities, thus improving citizens’ quality of life. However, the heterogeneity of domains, systems, and data types makes the definition and integration of data a challenging task. An aspect to be considered in a data model for smart cities is the territory. The information generated in this environment is georeferenced from the city’s geographical space division, thus providing an element of data integration from different domains that belong to the same territory. The integration of data from multiple domains, considering the territory as an integrating element, allows multidimensional analyzes that enable more precise actions by providing a broader view of various information correlated from the geographic space of the city. To face the challenges related to the heterogeneity of the data, still making possible the correlation of information to the city’s territory, this paper presents LGeoSIM, a semantic information model for smart cities as a means of promoting interoperability and enabling analyzes considering multiple domains. LGeoSIM serves as an outline that uses ontologies and Linked Data to facilitate the semantic search and multidimensional analysis of data modeled according to the model considering the territory as an integrating element of this data. LGeoSIM was implemented as an information model of the middleware platform for smart cities SGeoL and evaluated using real data from education and health scenarios.