Gaining insight into user behaviour and systematically determing user location via Bluetooth low energy beacon optimisation
Conference paper
Benedict, S., Augusto, J. and Kacar. O. 2024. Gaining insight into user behaviour and systematically determing user location via Bluetooth low energy beacon optimisation. 20th International Conference on Intelligent Environments (IE2024). Ljubljana, Slovenia 17 - 20 Jun 2024 IEEE. https://doi.org/10.1109/IE61493.2024.10599920
Type | Conference paper |
---|---|
Title | Gaining insight into user behaviour and systematically determing user location via Bluetooth low energy beacon optimisation |
Authors | Benedict, S., Augusto, J. and Kacar. O. |
Abstract | The multiuser challenge within the field of Intelligent Environments, specifically concerning Indoor Positioning systems needs to be addressed. Solving this challenge is paramount for enabling customised services in indoor locations. This investigation aims to distinguish between multiple users in an Intelligent Environment and identify their specific locations at a given time by employing a visual interface to deploy localised and personalised services to specific individuals in real-time. The investigation is conducted in the Smart Spaces Lab of Middlesex University London (i.e., a fully functional Intelligent Environment). The investigation leverages the Lab's existing technology and uses BLE Beacons with a novel placement approach to complete the User Location challenge. User Data was also generated in the process, giving rise to many insights. On the other hand, Machine Learning was utilised to predict User Activity using the generated Data. The study also offers insight into the latest research concerning indoor positioning systems and their approaches. Additionally, the investigation benchmarks its approaches against the methods published in recent literature and reviews the limitations of this investigation, emphasising future work. Video-based evidence is provided to establish the investigation's authenticity and complement the description in this paper. |
Keywords | Intelligent Environments; Machine Learning; Activity Recognition; Data Generation |
Sustainable Development Goals | 9 Industry, innovation and infrastructure |
Middlesex University Theme | Creativity, Culture & Enterprise |
Research Group | Research Group on Development of Intelligent Environments |
Conference | 20th International Conference on Intelligent Environments (IE2024) |
Proceedings Title | 2024 International Conference on Intelligent Environments (IE) |
ISSN | 2469-8792 |
Electronic | 2472-7571 |
ISBN | |
Electronic | 9798350386790 |
Paperback | 9798350386806 |
Publisher | IEEE |
Publication dates | |
01 Jun 2024 | |
Online | 17 Jul 2024 |
Publication process dates | |
Submitted | 03 Jan 2024 |
Accepted | 20 Feb 2024 |
Deposited | 08 May 2024 |
Output status | Published |
Accepted author manuscript | File Access Level Open |
Copyright Statement | © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Digital Object Identifier (DOI) | https://doi.org/10.1109/IE61493.2024.10599920 |
Web address (URL) of conference proceedings | https://ieeexplore.ieee.org/xpl/conhome/10599852/proceeding |
Language | English |
https://repository.mdx.ac.uk/item/135zyq
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