Location-Based Services with iBeacon Technology

Kouhne, Markus; Sieck, Jürgen

doi:10.1109/aims.2014.58

Cited by 67 publications

(34 citation statements)

References 1 publication

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“…A low-cost, reliable, and crowd-based technology using individuals' mobile devices as receiving stations to map and locate lost items used in accordance the iBeacon technology [5][6][7]. The iBeacon technology is able to emit Bluetooth 4.0 [15][16][17][18] signals and is based on physical proximity sensor devices known as beacons.…”

Section: Introductionmentioning

confidence: 99%

An IOT-Based Crowd Sourcing System for Object Tracking and Information Sharing

Qu¹,

Sun²

2019

IJAIA

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Technological advancements has offered many solutions to the important current issues such as the growing numbers ofrunaway children, wandering Alzheimer's patients and lost pets in the society, yet most branches of current technologiesare not capable of encompassingallof these key problems. My researchproposes a solution that is practical, durable and reliable-a proximity sensor device powered by other users in the area with a process known as "crowdsourcing", by using their mobile devices as receiving stations of the service, extensively increasing the effectiveness of this service in especially urban and suburban areas where there is a high population density.

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Section: Introductionmentioning

confidence: 99%

An IOT-Based Crowd Sourcing System for Object Tracking and Information Sharing

Qu¹,

Sun²

2019

IJAIA

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“…However, these techniques do not consider architectural problems caused by real-time searching or efficiency of mobile networks. Considering applications with location-based services such as iBeacon [16], the existing sensor searching techniques are not sufficient for real-time reaction when the mobile device receives information from a sensor close to the user. Because the mobile device needs to receive sensor information whenever it is requested, the mobile network QoS influences services to be provided successfully to the user.…”

Section: International Journal Of Distributed Sensor Networkmentioning

confidence: 99%

Path Prediction Method for Effective Sensor Filtering in Sensor Registry System

Lee

Jeong

Baik

et al. 2015

International Journal of Distributed Sensor Networks

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The Internet of Things (IoT) has emerged and several issues have arisen in the area such as sensor registration and management, semantic interpretation and processing, and sensor searching and filtering in Wireless Sensor Networks (WSNs). Also, as the number of sensors in an IoT environment increases significantly, sensor filtering becomes more important. Many sensor filtering techniques have been researched. However most of them do not consider real-time searching and efficiency of mobile networks. In this paper, we suggest a path prediction approach for effective sensor filtering in Sensor Registry System (SRS). SRS is a sensor platform to register and manage sensor information for sensor filtering. We also propose a method for learning and predicting user paths based on the Collective Behavior Pattern. To improve prediction accuracy, we consider a time feature to measure weights and predict a path. We implement the method and the implementation and its evaluation confirm the improvement of time and accuracy for processing sensor information.

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“…The IoT platform can be connected with different urban services such as a transport service, a bus service, and a local information service. The smart block can be effectively developed by iBeacon that is a Bluetooth low energy (BLE, Bluetooth 4.0) device developed by Apple [17] [18]. This iBeacon can "broadcast their unique identifiers to nearby portable mobile devices or objects and trigger a location-based action on these devices or objects" without "paired connection with the mobile devices" [19].…”

Section: System Structure and Data Flowmentioning

confidence: 99%