New adaptive techniques for Location of Things data quality management
The Location of Things (LoT) entails the collection of massive amounts of mobility data, which are then processed and transmitted among heterogeneous data nodes in a decentralised architecture. Since traditional centralised data quality management techniques can't cope with such LoT processes, data quality management for the LoT remains a challenge. The EU-funded MALOT project intends to design a set of new techniques that can adapt to the decentralised and heterogeneous LoT architecture. This will involve developing a core model for assessing mobility data quality at decentralised and dynamic data nodes, effective quality-aware data enhancement algorithms and a mechanism for the optimal scheduling of quality management tasks among relevant nodes. The project’s work will contribute to the innovation of Europe’s Internet of Things and expand its applications.
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