scholarly journals An Ensemble Filter for Indoor Positioning in a Retail Store Using Bluetooth Low Energy Beacons

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4550 ◽  
Author(s):  
Vasilis Stavrou ◽  
Cleopatra Bardaki ◽  
Dimitris Papakyriakopoulos ◽  
Katerina Pramatari
Keyword(s):  
Random Forest ◽  
Indoor Localization ◽  
Indoor Positioning ◽  
Retail Store ◽  
Low Energy ◽  
Location Based Services ◽  
Shopping Behavior ◽  
Multiple Sources ◽  
Bluetooth Low Energy ◽  
Product Categories

This paper has developed and deployed a Bluetooth Low Energy (BLE) beacon-based indoor positioning system in a two-floor retail store. The ultimate purpose of this study was to compare the different indoor positioning techniques towards achieving efficient position determination of moving customers in the retail store. The innovation of this research lies in its context (the retail store) and the fact that this is not a laboratory, controlled experiment. Retail stores are challenging environments with multiple sources of noise (e.g., shoppers’ moving) that impede indoor localization. To the best of the authors’ knowledge, this is the first work concerning indoor localization of consumers in a real retail store. This study proposes an ensemble filter with lower absolute mean and root mean squared errors than the random forest. Moreover, the localization error is approximately 2 m, while for the random forest, it is 2.5 m. In retail environments, even a 0.5 m deviation is significant because consumers may be positioned in front of different store shelves and, thus, different product categories. The more accurate the consumer localization, the more accurate and rich insights on the customers’ shopping behavior. Consequently, retailers can offer more effective customer location-based services (e.g., personalized offers) and, overall, better consumer localization can improve decision making in retailing.

WiFi and Bluetooth Low Energy Beacons for Indoor Positioning System

2019 ◽  
Vol 1 (2) ◽  
pp. 1-5
Author(s):  
Nurul Fatehah Zulkpli ◽  
Nor Azlina Ab. Aziz ◽  
Noor Ziela Abd Rahman ◽  
Rosli Besar
Keyword(s):  
Indoor Positioning ◽  
Low Energy ◽  
Location Based Services ◽  
Positioning System ◽  
Indoor Environments ◽  
Wireless Technologies ◽  
Bluetooth Low Energy ◽  
Advantages And Disadvantages ◽  
Performance Accuracy ◽  
Indoor Positioning System

Indoor Positioning System (IPS) is used to locate a person, an object or a location inside a building. IPS is important in providing location-based services, which has recently gain much popularity. The services ease visitors’ navigation at unfamiliar premises. Location-based services depend on the capability of IPS to accurately determine the location of the user, which is a challenging issue in indoor environments. Several wireless technologies are available. In this paper, two of the most widely used IPS technologies are reviewed which are, WiFi and Bluetooth low energy (BLE). Their advantages and disadvantages are reviewed and reported here. Comparison of the systems based on their performance, accuracy and limitations are presented as well.

scholarly journals Evaluation of Distance Error with Bluetooth Low Energy Transmission Model for Indoor Positioning

2021 ◽  
Author(s):  
Pichaya Supanakoon ◽  
Sathaporn Promwong
Keyword(s):  
Path Loss ◽  
Multipath Fading ◽  
Indoor Positioning ◽  
Low Energy ◽  
Location Based Services ◽  
Loss Model ◽  
Bluetooth Low Energy ◽  
Path Loss Model ◽  
Distance Error ◽  
Proposed Model

Currently, an indoor positioning is a challenge application for location-based services (LBS) and proximity-based services (PBS). However, the indoor channel has dense multipath fading, causing more distance error than outdoor positioning. In this paper, the distance error analysis model is proposed for indoor positioning. The indoor channel is modeled as the sum of path loss model and multipath fading model. The path loss model is a linear regression model (LRM) based on Friis’ transmission formula, used for estimating the distance from received signal strength (RSS). The multipath fading is a Gaussian statistical model with zero mean, used for characterizing the multipath fading effect. The normalized distance error is evaluated and defined. The indoor channel with Bluetooth low energy (BLE) beacons is measured and compared with the proposed model. From the results, the normalized distance error obtained from the proposed model corresponds very well to measurement. This proposed model can be used as a tool for designing an indoor positioning system to obtain the specific distance error.

scholarly journals Indoor Positioning for Monitoring Older Adults at Home: Wi-Fi and BLE Technologies in Real Scenarios

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 728 ◽  
Author(s):  
Raul Montoliu ◽  
Emilio Sansano ◽  
Arturo Gascó ◽  
Oscar Belmonte ◽  
Antonio Caballer
Keyword(s):  
Older Adults ◽  
Indoor Localization ◽  
Indoor Positioning ◽  
Low Energy ◽  
Real Case ◽  
Bluetooth Low Energy ◽  
Localization System ◽  
Localization Systems ◽  
At Home

This paper presents our experience on a real case of applying an indoor localization system for monitoring older adults in their own homes. Since the system is designed to be used by real users, there are many situations that cannot be controlled by system developers and can be a source of errors. This paper presents some of the problems that arise when real non-expert users use localization systems and discusses some strategies to deal with such situations. Two technologies were tested to provide indoor localization: Wi-Fi and Bluetooth Low Energy. The results shown in the paper suggest that the Bluetooth Low Energy based one is preferable in the proposed task.

scholarly journals WiFi and Bluetooth Low Energy Beacons for Indoor Positioning System

2019 ◽  
Vol 1 (2) ◽  
pp. 1-5
Author(s):  
Nurul Fatehah Zulkpli ◽  
Nor Azlina Ab. Aziz ◽  
Noor Ziela Abd Rahman ◽  
Rosli Besar
Keyword(s):  
Indoor Positioning ◽  
Low Energy ◽  
Location Based Services ◽  
Positioning System ◽  
Indoor Environments ◽  
Wireless Technologies ◽  
Bluetooth Low Energy ◽  
Advantages And Disadvantages ◽  
Challenging Issue ◽  
Indoor Positioning System

Indoor Positioning System (IPS) is used to locate a person, an object or a location inside a building. IPS is important in providing location-based services, which hasrecently gainmuchpopularity. The services ease visitors’ navigation at unfamiliar premises. Location-based services depend on the capability of IPS to accurately determine the location of the user, which is a challenging issue in indoor environments. Several wireless technologies are available. In this paper, two of the most widely used IPS technologies are reviewed which are, WiFi and Bluetooth low energy (BLE). Their advantages and disadvantages are reviewed and reported here.Comparison of the systemsbased on theirperformance, accuracy and limitations are presented as well.

scholarly journals Indoor Bluetooth Low Energy Dataset for Localization, Tracking, Occupancy, and Social Interaction

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4462 ◽  
Author(s):  
Paolo Baronti ◽  
Paolo Barsocchi ◽  
Stefano Chessa ◽  
Fabio Mavilia ◽  
Filippo Palumbo
Keyword(s):  
Social Interaction ◽  
Indoor Localization ◽  
Meaningful Use ◽  
Research Area ◽  
Low Energy ◽  
Bluetooth Low Energy ◽  
Novel Technologies ◽  
Wide Availability ◽  
Low Costs ◽  
Open Datasets

Indoor localization has become a mature research area, but further scientific developments are limited due to the lack of open datasets and corresponding frameworks suitable to compare and evaluate specialized localization solutions. Although several competitions provide datasets and environments for comparing different solutions, they hardly consider novel technologies such as Bluetooth Low Energy (BLE), which is gaining more and more importance in indoor localization due to its wide availability in personal and environmental devices and to its low costs and flexibility. This paper contributes to cover this gap by: (i) presenting a new indoor BLE dataset; (ii) reviewing several, meaningful use cases in different application scenarios; and (iii) discussing alternative uses of the dataset in the evaluation of different positioning and navigation applications, namely localization, tracking, occupancy and social interaction.

Bluetooth Low-Energy-Based Applications

2018 ◽  
pp. 95-112
Author(s):  
Smita Sanjay Ambarkar ◽  
Rakhi Dattatraya Akhare
Keyword(s):  
Indoor Localization ◽  
Low Energy ◽  
Smart Devices ◽  
The Internet ◽  
Bluetooth Low Energy ◽  
Iot Applications ◽  
Proximity Detection ◽  
Battery Power ◽  
Commercial Market ◽  
The Internet Of Things

This chapter focuses on the comprehensive contents of various applications and principles related to Bluetooth low energy (BLE). The internet of things (IoT) applications like indoor localization, proximity detection problem by using Bluetooth low energy, and enhancing the sales in the commercial market by using BLE have the same database requirement and common implementation idea. The real-world applications are complex and require intensive computation. These computations should take less time, cost, and battery power. The chapter mainly focuses on the usage of BLE beacons for indoor localization. The motive behind the study of BLE devices is that it is supported by mobile smart devices that augment its application exponentially.

STUPEFY: Set-Valued Box Particle Filtering for Bluetooth Low Energy-Based Indoor Localization

2019 ◽  
Vol 26 (12) ◽  
pp. 1773-1777 ◽  
Author(s):  
Parvin Malekzadeh ◽  
Arash Mohammadi ◽  
Mihai Barbulescu ◽  
Konstantinos N. Plataniotis
Keyword(s):  
Particle Filtering ◽  
Indoor Localization ◽  
Low Energy ◽  
Bluetooth Low Energy
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