Machine learning for reliable outdoor wireless communication

Speaker: Wannes Meert

Company/ Institute: DTAI – KU Leuven (project partner: ToughComputing – Xtendit Solutions)

Event: 15th work meeting

Date: 25 February 2014


The goal of the IWT-KMO MuSE project is to improve outdoors communication through innovation. A frequently occurring problem is that helpdesks have a hard time to correctly diagnose issues raised (or not raised) by outdoor users. There are two main reasons for this: (1) Network issues or unstable connections are a source of discontent and aggravation but are not communicated to the helpdesk until they pile up and become a blocking issue; and (2) Insufficient quality of the data that is forwarded to find the root cause. In this project we try to tackle these issues by investigating techniques to model the expected network behaviour in a certain region and detect problems automatically in an early stage.

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