Thesis supervisor: Zsolt Tóth
Location of studies (in Hungarian): Debreceni Egyetem Informatikai Tudományok Doktori Iskola Abbreviation of location of studies: ITDI
Description of the research topic:
Project Description
Indoor positioning has gained attention over the past decades. Although there
is no single widely accepted solution for indoor positioning, there is a general
need for these systems in various scenarios. Indoor navigation systems are built
on indoor positioning systems and provide more abstract services such as route
finding. These systems can be deployed in huge public indoor environments
where people want to find their destination quickly and easily such ash in an
airport or a shopping mall. Indoor navigation systems would facilitate the life
of people with disability and many papers are focused on this topic in these
days.
Symbolic indoor positioning determines the location as a part of the building. Symbolic positions refer to a specific part of the building so this tasks
seems to be easier then exact positioning. On the other hand, the automatic
extraction of these symbolic positions and providing reliable positioning services
are still challenging. To the best of our knowledge, there is no symbolic indoor
positioning service which is widely available, reliable and based on WiFi RSSI
signals. The goal of this research it to analyze and use classification algorithms
for symbolic indoor positioning and create a reliable algorithm which considers
the topology of the building.
Tasks
The successful candidate will
• analyze the existing symbolic indoor positioning methods.
• compare these algorithm over an existing data set
• define an own benchmark for comparison of symbolic indoor positioning
techniques.
• extract topology information from various map formats.
• enhance classifiers with topology information in order to increase its reliability.
• take part in seminars and hold tutorials.
• publish the results in international journals and conferences.
Requirements
The successful candidate has
• a degree in Computer Science, Information Technology, Mathematics or
other related fields.
• a strong analytical skill.
• proficiency in at least one of the following programming languages: C/C++,
Java.
Expected Results
• New indoor positioning algorithms implemented and tested in the ILONA
System.
• publications at top venues
Deadline for application: 2021-11-15
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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