Tempcache: A database optimization algorithm for real-time data handling in indoor spatial environments
dc.contributor.author | Jayakody, J. | |
dc.contributor.author | Murray, Iain | |
dc.contributor.author | Hermann, J. | |
dc.contributor.author | Lokuliyana, S. | |
dc.contributor.author | Dunuwila, V. | |
dc.date.accessioned | 2018-12-13T09:16:03Z | |
dc.date.available | 2018-12-13T09:16:03Z | |
dc.date.created | 2018-12-12T02:46:41Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Jayakody, J. and Murray, I. and Hermann, J. and Lokuliyana, S. and Dunuwila, V. 2018. Tempcache: A database optimization algorithm for real-time data handling in indoor spatial environments, pp. 346-351. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/73276 | |
dc.identifier.doi | 10.1109/ICCSE.2018.8468732 | |
dc.description.abstract |
© 2018 IEEE. The unstable arrangement of modern indoor environments has made navigation within buildings a difficult task. Hence, this paper introduces the AccessBIM framework, which is an efficient real-time indoor navigation system that facilitates in generating a real-time indoor map by crowdsourcing spatial data through the sensors available in mobile devices of navigators. The framework is equipped with a database optimization algorithm known as 'Tempcache' which reduces the time and cost of searching data by examining the AccessBIM database for previously navigated paths, thus enabling faster data retrieval through efficient query processing. A simulation of a virtual environment similar to an actual indoor environment was used to test the algorithm. The significance of the algorithm was validated by comparing the total map generation time before and after the algorithm was applied for which the results demonstrated a reduction in map generation time with the use of the algorithm. The framework is also capable of capturing localization information with the support of i-Beacons which is then stored in a cloud server. | |
dc.title | Tempcache: A database optimization algorithm for real-time data handling in indoor spatial environments | |
dc.type | Conference Paper | |
dcterms.source.startPage | 346 | |
dcterms.source.endPage | 351 | |
dcterms.source.title | 13th International Conference on Computer Science and Education, ICCSE 2018 | |
dcterms.source.series | 13th International Conference on Computer Science and Education, ICCSE 2018 | |
dcterms.source.isbn | 9781538654958 | |
curtin.accessStatus | Fulltext not available | |
curtin.faculty | Faculty of Science and Engineering |
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |