| Abstract |
Within a smart city concept, it is possible to combine a large number of information sources that has spatio-temporal characteristics. The complexity of such a combination lies in the high heterogeneity of information, the need to use spatial and temporal characteristics, as well as formats for presenting such information. To date, there are information platforms for smart city sources organization that allow combining heterogeneous data sources, however, in the process of combining, human participation is still required to establish an unambiguous correspondence and process space-time characteristics. The paper proposes an approach based on a microservice architecture, in which each data source is mapped to a microservice, which presents an ontological data model of the source. When forming a query, data is sampled from sources and integrated based on spatial characteristics for subsequent analysis. As an example, the paper provides an analysis of data on road accidents in St. Petersburg, Russia since 2019 in order to determine accident-dangerous sections of roads and the main causes of accidents. The result is accidents clusters obtained by combining accidents data, road types and weather conditions in the accidents area. |
