Applied PhD 2019: MISTic: Multi-source trend analytics for intelligent transportation systems

The main research objectives are (1) to investigate hierarchical and adaptive multi-source data and model integration techniques enabling the combination of information from heterogeneous sources, (2) to research knowledge propagation techniques within and across data sources, (3) to explore methods for estimating the quality of data fusion, (4) to research methods enabling context-aware situation profiling, interpretation and evolution prediction, and (5) to realize and validate
a proof-of-concept trend analytics engine and demonstrate its potential via realistic use cases.