MALOT Project
MALOT Project

I am pleased to announce that my MSCA (Marie Skłodowska-Curie Actions) proposal MALOT: Managing Mobility Data Quality for Location of Things hosted by Aalborg University has been approved.

Thanks to the fundraising department of Aalborg University and my supervisors for their valuable suggestions on this work.

The abstract of the proposal is as follows.

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. Specifically, MALOT includes 1) a core model for assessing mobility data quality at individual LoT nodes; 2) effective data enhancement algorithms based on the quality model for resolving data heterogeneity and inconsistency; (3) a task scheduling mechanism for improving overall efficiency of data quality management in LoT.

This fellowship will last for 24 months, focusing on resolving some open issues in management of Location of Things data.