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  • Pozycja
    Graph-Supported Preparation of GIS Machine Learning Datasets
    (Wydawnictwo Politechniki Łódzkiej, 2023) Ernst, Sebastian
    The paper presents an approach to preparing spatial (GIS) datasets for machine learning models, and using graph structure to materialise and utilise the results. The presented work is based on the Spatially-Triggered Graph Transformations (STGT) methodology, previously used for many realworld applications, e.g. in the area of smart cities. A workflow using OSM data is presented, aimed at improving the granularity and semantic annotation of map features.
  • Pozycja
    Lessons Learned from a Smart City Project with Citizen Engagement
    (Wydawnictwo Politechniki Łódzkiej, 2023) Ernst, Sebastian; Zaworski, Konrad; Sokołowski, Piotr; Salwa, Grzegorz
    The paper discusses the experiences gained in a joint research project by AGH and the commune of Siechnice. Two main areas are discussed: collecting data from heterogenous sensor devices as well as input from citizens, and development of analytic procedures in a way which guarantees integration between day-to-day and research operations. The most prominent outcomes of the project include the development of a living lab as well as automation of multi-aspect inference, which would normally have to be carried out by a team of experts.