New adaptive techniques for Location of Things data quality management


Location of Things (LoT) is an Internet of Things paradigm for mobility analytics. In LoT, massive mobility data is being gathered, processed and transmitted among heterogeneous data nodes in a decentralized architecture. Thus, managing data quality for LoT has become a prominent challenge as traditional techniques cannot cope with the aforementioned characteristics of LoT. In our project MALOT, we aim at designing a set of new techniques to manage data quality for LoT effectively and efficiently. MALOT includes

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Principal Investigator: Huan Li
Project Supervisor: Prof. Hua Lu
Host: Aalborg University

EU MSCA

This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No.882232.

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