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Real-time detection of attendance at a venue using mobile devices
Author(s)
Sagboze, Konzi Olivier
Date Issued
2017
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
The implosion of the mobile phones, mobile applications and social media in recent years has triggered a great interest for more dedicated user-generated contents. Mobile users being the focal point, these modern virtual platforms depend on and live for collecting, structuring and manipulating the very fine-grained details about users' day-to-day activities.
Since every human activity takes place in a geographical context, location information ranks high among the set of data to gather about user's daily life. User's specific location details can help filter content to serve and retrieve from them. Therefore, location-based services have been developed and successfully integrated into most virtual platforms in the quest for these precious data.
However, location-based services do not fulfil all requirements. They depend on a range of positioning systems which show numerous limitations. None of the existing positioning systems is perfectly accurate. Today, it is therefore difficult to pinpoint a user in a venue using location-based services.
Nevertheless, with the set of existing technology and techniques, it is possible to estimate and track users’ whereabouts in real-time. Providing the best possible estimation of user's position within a given venue can help achieve better user engagement. Depending on the gap of accuracy, the end result may actually match the outcome expected from perfectly accurate positioning systems.
In this work, the focus is to develop a prototype positioning system which provides the best estimation of user's position in real-time in relation to a targeted venue or location. Through a series of research and comparison study, the most suited technology and techniques are objectively selected to build the intended prototype.
The challenge of indoor positioning is also addressed in this work – bearing in mind the fact that this prototype is set to work accurately and efficiently in any geographical location and structure. The prototype is evaluated according to a set of predefined standard metrics, and theories are extracted to grow knowledge about this trending topic.
Since every human activity takes place in a geographical context, location information ranks high among the set of data to gather about user's daily life. User's specific location details can help filter content to serve and retrieve from them. Therefore, location-based services have been developed and successfully integrated into most virtual platforms in the quest for these precious data.
However, location-based services do not fulfil all requirements. They depend on a range of positioning systems which show numerous limitations. None of the existing positioning systems is perfectly accurate. Today, it is therefore difficult to pinpoint a user in a venue using location-based services.
Nevertheless, with the set of existing technology and techniques, it is possible to estimate and track users’ whereabouts in real-time. Providing the best possible estimation of user's position within a given venue can help achieve better user engagement. Depending on the gap of accuracy, the end result may actually match the outcome expected from perfectly accurate positioning systems.
In this work, the focus is to develop a prototype positioning system which provides the best estimation of user's position in real-time in relation to a targeted venue or location. Through a series of research and comparison study, the most suited technology and techniques are objectively selected to build the intended prototype.
The challenge of indoor positioning is also addressed in this work – bearing in mind the fact that this prototype is set to work accurately and efficiently in any geographical location and structure. The prototype is evaluated according to a set of predefined standard metrics, and theories are extracted to grow knowledge about this trending topic.
Additional information
Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2017.
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211077763-Sagboze-Konzi Olivier-MTech-Information-Technology-FID-2018.pdf
Description
Thesis
Size
2.04 MB
Format
Adobe PDF
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