Bluetooth Based Indoor Positioning Using Machine Learning Algorithms

Sthapit, Pranesh; Gang, Hui-Seon; Pyurr, Jae-Young

doi:10.1109/icce-asia.2018.8552138

Cited by 47 publications

(31 citation statements)

References 7 publications

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“…More recent research introduces an improvement to the triangulation method by using machine learning algorithms [ 13 ]. The setup includes a specific deployment of beacons along a path, that continuously transmit broadcast signals in a typical order.…”

Section: Related Workmentioning

confidence: 99%

Developing a Solution for Mobility and Distribution Analysis Based on Bluetooth and Artificial Intelligence

Minea

Dumitrescu

Costea

et al. 2020

Sensors

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The purpose of this research was to develop a simple, cost-effective, but enough efficient solution for locating, tracking and distribution analysis of people and/or vehicle flowing, based on non-intrusive Bluetooth sensing and selective filtering algorithms employing artificial intelligence components. The solution provides a tool for analyzing density of targets in a specific area, useful when checking contact proximities of a target along a route. The principle consists of the detection of mobile devices that use active Bluetooth connections, such as personal notebooks, smartphones, smartwatches, Bluetooth headphones, etc. to locate and track their movement in the dedicated area. For this purpose, a specific configuration of three BT sensors is used and RSSI levels compared, based on a combination of differential location estimates. The solution may also be suited for indoor localization where GPS signals are usually weak or missing; for example, in public places such as subway stations or trains, hospitals, airport terminals and so on. The applicability of this solution is estimated to be vast, ranging from travel and transport information services, route guidance, passenger flows tracking, and path recovery for persons suspected to have SARS-COV2 or other contagious viruses, serving epidemiologic enquiries. The specific configuration of Bluetooth detectors may be installed either in a fixed location, or in a public transport vehicle. A set of filters and algorithms for triangulation-based location of detected targets and movement tracking, based on artificial intelligence is employed. When applied in the public transport field, this setup can be also developed to extract additional information on traffic, such as private traffic flowing, or passenger movement patterns along the vehicle route, improved location in absence of GPS signals, etc. Field tests have been carried out for determining different aspects concerning indoor location accuracy, reliability, selection of targets and filtering. Results and possible applications are also presented in the final section of the paper.

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Section: Related Workmentioning

confidence: 99%

Developing a Solution for Mobility and Distribution Analysis Based on Bluetooth and Artificial Intelligence

Minea

Dumitrescu

Costea

et al. 2020

Sensors

View full text Add to dashboard Cite

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“…The research community is also currently exploring the usability of BLE for location tracking and indoor positioning systems [49][50][51][52][53]. For example, BLE proximity beacons can be utilized for determining the location of buses without requiring the usage of any Global Positioning System (GPS) devices.…”

Section: Location Trackingmentioning

confidence: 99%

“…There is also a lot of focus on developing new fingerprinting-based algorithms to address issues of accuracy, precision, and time complexity when implementing positioning using BLE-beacons [52]. Efforts are being focused on improving the time-complexities of these algorithms [52] as well as employing machine learning algorithms together with BLE to improve location accuracy [53]. Some BLE systems have shown an improvement in the positioning accuracy by about 15% compared to other positioning alternatives such as GPS, and so on [54].…”

Section: Location Trackingmentioning

confidence: 99%

25 Years of Bluetooth Technology

2019

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Bluetooth technology started off as a wireless, short-range cable replacement technology but it has undergone significant developments over the last two decades. Bluetooth radios are currently embedded in almost all computing devices including personal computers, smart phones, smart watches, and even micro-controllers. For many of us, Bluetooth is an essential technology that we use every day. We provide an insight into the history of Bluetooth and its significant design developments over the last 25 years. We also discuss related issues (including security) and Bluetooth as a driving technology for the Internet of Things (IoT). Finally, we also present recent research results obtained with Bluetooth technology in various application areas.

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“…The vast majority of BLE-based applications still assume a star network topology while using BLE Beacons in broadcast mode [3][4][5][6][7][8][9]. To enhance the coverage of BLE 4 networks, hybrid mesh topologies extend the master-slave piconet concept into various interconnected scatternets via the fusion of star and mesh links [10].…”

Section: Introductionmentioning

confidence: 99%

Bluetooth Low Energy Mesh Networks: Survey of Communication and Security Protocols

Ghori

Wan

Sodhy

2020

Sensors

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Bluetooth Low Energy (BLE) Mesh Networks enable flexible and reliable communications for low-power Internet of Things (IoT) devices. Most BLE-based mesh protocols are implemented as overlays on top of the standard Bluetooth star topologies while using piconets and scatternets. Nonetheless, mesh topology support has increased the vulnerability of BLE to security threats, since a larger number of devices can participate in a BLE Mesh network. To address these concerns, BLE version 5 enhanced existing BLE security features to deal with various authenticity, integrity, and confidentiality issues. However, there is still a lack of detailed studies related to these new security features. This survey examines the most recent BLE-based mesh network protocols and related security issues. In the first part, the latest BLE-based mesh communication protocols are discussed. The analysis shows that the implementation of BLE pure mesh protocols remains an open research issue. Moreover, there is a lack of auto-configuration mechanisms in order to support bootstrapping of BLE pure mesh networks. In the second part, recent BLE-related security issues and vulnerabilities are highlighted. Strong Intrusion Detection Systems (IDS) are essential for detecting security breaches in order to protect against zero-day exploits. Nonetheless, viable IDS solutions for BLE Mesh networks remain a nascent research area. Consequently, a comparative survey of IDS approaches for related low-power wireless protocols was used to map out potential approaches for enhancing IDS solutions for BLE Mesh networks.

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Bluetooth Based Indoor Positioning Using Machine Learning Algorithms

Cited by 47 publications

References 7 publications

Developing a Solution for Mobility and Distribution Analysis Based on Bluetooth and Artificial Intelligence

Developing a Solution for Mobility and Distribution Analysis Based on Bluetooth and Artificial Intelligence

25 Years of Bluetooth Technology

Bluetooth Low Energy Mesh Networks: Survey of Communication and Security Protocols

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