scholarly journals A Low Energy IoT Application Using Beacon for Indoor Localization

2021 ◽  
Vol 11 (11) ◽  
pp. 4902
Author(s):  
Francesco Pascale ◽  
Ennio Andrea Adinolfi ◽  
Massimiliano Avagliano ◽  
Venanzio Giannella ◽  
Andres Salas
Keyword(s):  
Internet Of Things ◽  
Indoor Localization ◽  
Low Energy ◽  
Experimental Results ◽  
Bluetooth Low Energy ◽  
Indoor Location ◽  
Innovative Method

In recent years, a great number of applications in Internet of Things (IoT) have been developed. In this context, many methodologies and technologies are used for several frameworks, including indoor localization. In this field, as highlighted in recent years, one of the most important aims of modern indoor applications in IoT is to identify how to manage and correctly convey people flow. This study aims to investigate the most common methods, technologies and applications for indoor localization in IoT and analyze the major systems currently in use and the application of these solutions to actual conditions. Following this, we propose an innovative method to detect people flow in indoor location. Based on Bluetooth low energy (BLE) technology, in this paper we analyze the possibility to use our system for many kinds of applications. The first experimental results show good performance of our system.

RFID, NFC, Beacons, and the Infrastructures of Logistical Locative Media

2020 ◽  
pp. 474-486
Author(s):  
Jordan Frith
Keyword(s):  
Internet Of Things ◽  
Radio Frequency Identification ◽  
Near Field ◽  
Low Energy ◽  
Near Field Communication ◽  
Rfid Tags ◽  
Bluetooth Low Energy ◽  
Locative Media ◽  
Frequency Identification ◽  
Machine Readable

The phrase the Internet of things was originally coined in a 1999 presentation about attaching radio frequency identification (RFID) tags to individual objects. These tags would make the objects machine-readable, uniquely identifiable, and, most importantly, wirelessly communicative with infrastructure. This chapter evaluates RFID as a piece of mobile communicative infrastructure, and it examines two emerging forms: near-field communication (NFC) and Bluetooth low-energy beacons. The chapter shows how NFC and Bluetooth low-energy beacons may soon move some types of RFID to smartphones, in this way evolving the use of RFID in payment and transportation and enabling new practices of post-purchasing behaviors.

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

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.

scholarly journals From Sensor Networks to Internet of Things. Bluetooth Low Energy, a Standard for This Evolution

Sensors ◽  
2017 ◽  
Vol 17 (2) ◽  
pp. 372 ◽  
Author(s):  
Diego Hortelano ◽  
Teresa Olivares ◽  
M. Ruiz ◽  
Celia Garrido-Hidalgo ◽  
Vicente López
Keyword(s):  
Sensor Networks ◽  
Internet Of Things ◽  
Low Energy ◽  
Bluetooth Low Energy
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