dc.contributor.author | Okike, Ivy Ijeoma | |
dc.date.accessioned | 2022-10-13T10:44:39Z | |
dc.date.available | 2022-10-13T10:44:39Z | |
dc.date.issued | 2019-07-24 | |
dc.identifier.uri | http://hdl.handle.net/2299/25810 | |
dc.description.abstract | Indoor localisation of people and objects has been a focus of research studies for several decades because of its great advantage to several applications. Accuracy has always been a challenge because of the uncertainty of the employed sensors. Several technologies have been proposed and researched, however, accuracy still represents an issue.
Today, several sensor technologies can be found in indoor environments, some of which are economical and powerful, such as Wi-Fi. Meanwhile, Smartphones are typically present indoors because of the people that carry them along, while moving about within rooms and buildings. Furthermore, vehicles such as mobility scooters can also be present indoor to support people with mobility impairments, which may be equipped with low-cost sensors, such as wheel encoders.
This thesis investigates the localisation of mobility scooters operating indoor. This represents a specific topic as most of today's indoor localisation systems are for pedestrians. Furthermore, accurate indoor localisation of those scooters is challenging because of the type of motion and specific behaviour.
The thesis focuses on improving localisation accuracy for mobility scooters and on the use of already available indoor sensors. It proposes a combined use of Wi-Fi, Smartphone IMU and wheel encoders, which represents a cost-effective energy-efficient solution.
A method has been devised and a system has been developed, which has been experimented on different environment settings. The outcome of the experiments are presented and carefully analysed in the thesis. The outcome of several trials demonstrates the potential of the proposed solutions in reducing positional errors significantly when compared to the state-of-the-art in the same area. The proposed combination demonstrated an error range of 0.35m - 1.35m, which can be acceptable in several applications, such as some related to assisted living. 3
As the proposed system capitalizes on the use of ubiquitous technologies, it opens up to a potential quick take up from the market, therefore being of great benefit for the target audience. | en_US |
dc.language.iso | en | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.rights | Attribution 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | * |
dc.subject | RSSI | en_US |
dc.subject | Localisation | en_US |
dc.subject | WTP-HAMS | en_US |
dc.subject | Trilateration | en_US |
dc.subject | mobility scooters | en_US |
dc.title | Indoor Localisation of Scooters from Ubiquitous Cost-Effective Sensors: Combining Wi-Fi, Smartphone and Wheel Encoders | en_US |
dc.type | info:eu-repo/semantics/doctoralThesis | en_US |
dc.identifier.doi | doi:10.18745/th.25810 | * |
dc.identifier.doi | 10.18745/th.25810 | |
dc.type.qualificationlevel | Doctoral | en_US |
dc.type.qualificationname | PhD | en_US |
dcterms.dateAccepted | 2019-07-24 | |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |
rioxxterms.version | NA | en_US |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
rioxxterms.licenseref.startdate | 2022-10-13 | |
herts.preservation.rarelyaccessed | true | |
rioxxterms.funder.project | ba3b3abd-b137-4d1d-949a-23012ce7d7b9 | en_US |