Using iBeacon for intelligent in-room presence detection

Yang, Yang; Li, Zhouchi; Pahlavan, Kaveh

doi:10.1109/cogsima.2016.7497808

Cited by 13 publications

(3 citation statements)

References 9 publications

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“…Without using an internet connection, the library user gets the necessary information on the mobile app. In [18], an in-room presence detection system is introduced to automate the attendance collection of conferences or courses. There are several works related to smart office management using mobile apps available in recent works [4] [19].…”

Section: Related Workmentioning

confidence: 99%

Implementation and Analysis of a Smart Team Management System Using iOS Devices As iBeacon

Sindhumol

2020

Int. J. Interact. Mob. Technol.

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<p class="0abstract">A cost-effective smart team management system using iOS devices as iBeacon for better task monitoring and presence detection is proposed in this work. It is designed to maximum utilize the proximity information offered by iOS devices through iBeacon integration. In addition to this positioning service, iOS core location framework, geofencing and push notifications features are also included in this work, to create a productive environment in an organization. Along with the employee tracking and task monitoring features, the proposed application provides the typical project management services like task allocation and notification, instant chat, status report, and employee log. On entering the iBeacon range, daily task details and announcements from all associated teams will be available in team member devices. The system is connected to a server for productive team management, and peer to peer communication is utilized for instant exchange of information. An experimental evaluation to study the effect of interference, obstacles, and measured power on received signal strength and accuracy of the proposed iBeacon is also conducted. The observed results positively recommend the proposed app as an efficient iBeacon application for project management.</p>

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Section: Related Workmentioning

confidence: 99%

Implementation and Analysis of a Smart Team Management System Using iOS Devices As iBeacon

Sindhumol

2020

Int. J. Interact. Mob. Technol.

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“…An iBeacon information advertising provides a UUID (Universally Unique IDentifier) (16 bytes), a Major (2 bytes) and a Minor (2 bytes), which can be customized to fit any possible application [23]. In addition to these values, when advertising an iBeacon will also return a value for "accuracy", the accuracy of the proximity in meters from the beacon (different from the actual distance from the beacon) and one for "RSSI" (received signal strngth indicator), the average value of the power level samples received from the beacon [28]. Since the "accuracy" returned by the beacon is influenced significantly by how each beacon is calibrated and by the presence of physical obstacles between the beacon itself and the devices receiving the broadcast, we chose not to use these values which often not accurate at all.…”

mentioning

confidence: 99%

“…• Ranging-when the system enters a region, it returns an approximative level of distance (immediate, near, far or unknown) and a received power level from all of the beacons therein [28] and a quite accurate value of distance from the center of the geofence (Figures 2 and 3).…”

mentioning

confidence: 99%

Beep4Me: Automatic Ticket Validation to Support Fare Clearing and Service Planning

Tuveri

Garau

Sottile

et al. 2022

Sensors

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An integrated transport service fare system, supported by an agreement for ticket revenue sharing among service providers, is an essential component to improve the experience of the users who can find single tickets for the integrated transport services they look for. A challenge is to find a model to share the revenue which all providers agree on. A solution is to adopt data-driven approaches where user-generated data are collected to extract information on the extent each transport service was used. This is consistently used. However, it suffers from incomplete data, as not all users always validate their ticket when checking out or when switching lines. We studied all technologies available to support automatic ticket validation in order to record when the users access and exit each service line. The contributions of this work are the following: we give an in-depth description of the inner workings of this novel approach describing how we take advantage of each technology; we present the developed solution (Beep4Me), which adds new functionalities to an existing mobile ticketing platform; and we describe our testing framework, which includes most cases users might encounter during a trip. Our results demonstrate how it is possible to collect key data related to validations which can be used first for clearing purposes and then for network planning/fleet optimization.

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RF Cloud for Cyberspace Intelligence

Pahlavan

Ying

et al. 2020

IEEE Access

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Wireless information networks have become a necessity of our day-today life. Over a billion Wi-Fi access points, hundreds of thousands of cell towers, and billions of IoT devices, using a variety of wireless technologies, create the infrastructure that enables this technology to access everyone, everywhere. The radio signal carrying the wireless information, propagates from antennas through the air and creates a radio frequency (RF) cloud carrying a huge amount of data that is commonly accessible by anyone. The big data of the RF cloud includes information about the transmitter type and addresses, embedded in the information packets; as well as features of the RF signal carrying the message, such as received signal strength (RSS), time of arrival (TOA), direction of arrival (DOA), channel impulse response (CIR), and channel state information (CSI). We can benefit from the big data contents of the messages as well as the temporal and spatial variations of their RF propagation characteristics to engineer intelligent cyberspace applications. This paper provides a holistic vision of emerging cyberspace applications and explains how they benefit from the RF cloud to operate. We begin by introducing the big data contents of the RF cloud. Then, we explain how innovative cyberspace applications are emerging that benefit from this big data. We classify these applications into three categories: wireless positioning systems, gesture and motion detection technologies, and authentication and security techniques. We explain how Wi-Fi, cell-tower, and IoT wireless positioning systems benefit from big data of the RF cloud. We discuss how researchers are studying applications of RF cloud features for motion, activity and gesture detection for human-computer interaction, and we show how authentication and security applications benefit from RF cloud characteristics.

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Using iBeacon for intelligent in-room presence detection

Cited by 13 publications

References 9 publications

Implementation and Analysis of a Smart Team Management System Using iOS Devices As iBeacon

Implementation and Analysis of a Smart Team Management System Using iOS Devices As iBeacon

Beep4Me: Automatic Ticket Validation to Support Fare Clearing and Service Planning

RF Cloud for Cyberspace Intelligence

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