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dc.contributor.authorJayakody, J.
dc.contributor.authorMurray, Iain
dc.contributor.authorHermann, J.
dc.contributor.authorLokuliyana, S.
dc.contributor.authorDunuwila, V.
dc.date.accessioned2018-12-13T09:12:56Z
dc.date.available2018-12-13T09:12:56Z
dc.date.created2018-12-12T02:46:41Z
dc.date.issued2018
dc.identifier.citationJayakody, J. and Murray, I. and Hermann, J. and Lokuliyana, S. and Dunuwila, V. 2018. Enhanced algorithmic implementation to assist real-time indoor map generation for vision impaired individuals, pp. 352-357.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/72282
dc.identifier.doi10.1109/ICCSE.2018.8468690
dc.description.abstract

© 2018 IEEE. The complexity of indoor environments has made navigation difficult for vision impaired individuals as well as individuals with clear vision. Although handheld mobility devices have been developed to assist the vision impaired in navigation, they are incapable of capturing parameters such as distance, angle and direction. This paper presents an appraised framework; the Accessible Building Information Model (AccessBIM), which could be used for generating an indoor map in real-time with the classification of real world objects and their locations. The AccessBIM database is equipped with two optimization algorithms; a database optimization algorithm that reduces the time of query execution through indexing, query re-writing, schema redesigning and a memory optimization algorithm known as 'Memcache'. Five scenarios were tested using a simulator to determine the accuracy of the map that is generated. The use of the two algorithms ensured that the real-time map generated through the data collected from the simulation environment was similar to the actual floor plan. Hence, it can be concluded that the AccessBIM framework has the potential to play an integral role in assistive technologies related to localization and mapping, thus significantly improving the quality of life for individuals with vision impairment.

dc.titleEnhanced algorithmic implementation to assist real-time indoor map generation for vision impaired individuals
dc.typeConference Paper
dcterms.source.startPage352
dcterms.source.endPage357
dcterms.source.title13th International Conference on Computer Science and Education, ICCSE 2018
dcterms.source.series13th International Conference on Computer Science and Education, ICCSE 2018
dcterms.source.isbn9781538654958
curtin.accessStatusFulltext not available
curtin.facultyFaculty of Science and Engineering


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