Join Operation for Semantic Data Enrichment of Asynchronous Time Series Data

In this paper, we present a novel framework for enriching time series data in smart cities by supplementing it with information from external sources via semantic enrichment. Our methodology effectively merges multiple into uniform series, while addressing difficulties such as quality, contextual information, and lapses. We demonstrate the efficacy of our method through case study Barcelona, which permitted use advanced analysis methods windowed cross-correlation peak picking. The resulting can be used to determine traffic patterns has potential uses other city sectors, air energy efficiency, public safety. Interactive dashboards enable stakeholders visualize summarize key insights patterns.