Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26921
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dc.contributor.advisorQUAX, Peter-
dc.contributor.advisorLAMOTTE, Wim-
dc.contributor.authorSchuurmans, Gert-
dc.date.accessioned2018-10-03T10:04:00Z-
dc.date.available2018-10-03T10:04:00Z-
dc.date.issued2018-
dc.identifier.urihttp://hdl.handle.net/1942/26921-
dc.description.abstractSince the beginning of the internet, there is a growth in the number of connected devices. This growth became even bigger after all kind of IoT devices were connected to the internet. These devices must have a low power consumption. To achieve low power consumption, all features of the device must be power efficient. This also includes the geolocation technique. Adding a GPS module would increase the power consumption too much for some applications. This master's thesis researched how the location of a target device could be estimated completely based on the measurements of the packets received from the target device. Multiple wireless communication technologies were compared to find a low-power, long range and cost efficient wireless communication technology to develop geolocation techniques for. Researching and testing a wide variety of geolocation techniques resulted in the RSSI to distance conversion technique delivering the most accurate location estimates. The Weighted Centroid technique performed almost as well and didn't require a sent packet to be received by all base stations. The TDOA technique required a timing accuracy which our setup couldn't deliver. LoRa resulted as the most suitable communication technology and the Weighted Centroid technique is the most suitable technique for LoRa.-
dc.format.mimetypeApplication/pdf-
dc.languagenl-
dc.publishertUL-
dc.titleTechniques to optimize geolocation for low-power devices-
dc.typeTheses and Dissertations-
local.format.pages0-
local.bibliographicCitation.jcatT2-
dc.description.notesmaster in de informatica-
local.type.specifiedMaster thesis-
item.fullcitationSchuurmans, Gert (2018) Techniques to optimize geolocation for low-power devices.-
item.accessRightsOpen Access-
item.fulltextWith Fulltext-
item.contributorSchuurmans, Gert-
Appears in Collections:Master theses
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