iBeacon Technology Research Articles

Smart Library Applications in Oman using iBeacon Technology: A Case Study

Academic universities, like other institutions, are experiencing some challenges related to the increasing progress in information and communications technology that the world is witnessing, which has had a clear impact on changing the nature and work of libraries and information centers. Smartphones are one of the most important and popular modern communications devices among users. Recently, it has witnessed increasing use of smartphone in various areas of life due to their connectivity to the Internet and the fact that their prices are affordable for everyone. With that consequences it became necessary to exploit this technology in the field of libraries to invest in exchanging information, providing various library services, and keeping up to date with the technological developments. Among a list of cutting edge technologies iBeacon is one of the modern technologies that has experienced an expansion in use on different scales recently including public library. Therefore, this study aimed to apply this iBeacon technology in the library of the University of Nizwa. Since the technology is new in Arab libraries, linking it to a smartphone application to help the users to have easy access to the location of the books on the shelves, as well as informing the user of new arrival /information that make them interested about the library. In addition to receiving notifications of upcoming activities offered by the library and the latest books that have arrived. Further, it will also reduce the burden on the employee by answering the user’s frequent questions on different library services. It will in fact, ensure the better services to the users and help the employee at the same time. Overall, this is will be an easy going path-way to achieve the required satisfaction with the library and its services from the end users and library authority. After extensive research and evaluation; in this paper; a number of suggestions has presented, such as the importance of the institution’s support for the library to adopt various modern technologies to facilitate its services and increase its efficiency through iBeacon.

Indoor Positioning and Navigation Model Based on Semantic Grid

Traditional GPS positioning technology cannot be used in indoor space. With the development of the new positioning technology and the Internet of things, the indoor mobile object positioning and navigation model have been the focus of the relevant research institutions at home and abroad. Based on this, indoor positioning technology was studied starting from Wi-Fi, RFID, and iBeacon technology in this paper. However, the accuracy of indoor positioning and navigation needs to be further improved. This paper presents a semantic space model based on artificial intelligence technology, through semantic pattern matching, semantic concept extension, semantic reasoning and semantic mapping, and interior semantic localization is realized. The indoor semantic network and indoor grid navigation model are constructed, and the indoor semantic path is modeled from time, location, user, and congestion. At the same time, the improved Term Frequency-Inverse Document Frequency is combined with the Hidden Markov Model to improve the accuracy of matching the stay area with the most likely location to visit and improve the accuracy of semantic annotation. It was found that the research on the indoor positioning and navigation model based on the semantic grid can realize the uniform expression of the complex spatial semantics of the theme, geometry, connectivity, and distance, which can promote the development of indoor positioning and navigation.

Understanding Social Behaviour in a Health-Care Facility from Localization Data: A Case Study.

The most frequent form of dementia is Alzheimer’s Disease (AD), a severe progressive neurological pathology in which the main cognitive functions of an individual are compromised. Recent studies have found that loneliness and living in isolation are likely to cause an acceleration in the cognitive decline associated with AD. Therefore, understanding social behaviours of AD patients is crucial to promote sociability, thus delaying cognitive decline, preserving independence, and providing a good quality of life. In this work, we analyze the localization data of AD patients living in assisted care homes to gather insights about the social dynamics among them. We use localization data collected by a system based on iBeacon technology comprising two components: a network of antennas scattered throughout the facility and a Bluetooth bracelet worn by the patients. We redefine the Relational Index to capture wandering and casual encounters, these being common phenomena among AD patients, and use the notions of Relational and Popularity Indexes to model, visualize and understand the social behaviour of AD patients. We leverage the data analyses to build predictive tools and applications to enhance social activities scheduling and sociability monitoring and promotion, with the ultimate aim of providing patients with a better quality of life. Predictions and visualizations act as a support for caregivers in activity planning to maximize treatment effects and, hence, slow down the progression of Alzheimer’s disease. We present the Community Behaviour Prediction Table (CBPT), a tool to visualize the estimated values of sociability among patients and popularity of places within a facility. Finally, we show the potential of the system by analyzing the Coronavirus Disease 2019 (COVID-19) lockdown time-frame between February and June 2020 in a specific facility. Through the use of the indexes, we evaluate the effects of the pandemic on the behaviour of the residents, observing no particular impact on sociability even though social distancing was put in place.

Development of SelfSpeaking Body Weight Scale for Visually Impaired People in Tanzania

Speaking weight scale is an important low vision health aid that measures and announces the measured weight. It is valuable in numerous applications such as Bathroom scale, Kitchen scale, and more. Different talking scales have been developed for the blind community. Many talking scales have language options for English, German, French, or Spanish. However, only limited work exists for Self speaking visually impaired community in EAC given the fact that no talking scale can announce weight in Self which is the common language in EAC. Therefore, this project aims to develop a Self-speaking weighing machine to assist visually impaired people in Tanzania. The developed device is divided into two major parts. On the front end of the design, sensors are used to capture weight parameters. The captured values are mapped onto a sequence of voice patterns. The back-end consists of transferring a sequence of voice patterns to a loudspeaker whereby the voice patterns are stored on an SD card. Finally, the developed device has been evaluated on several objects with known weights. The results show that the developed device accurately measures weight, displays weight, and announces it in the Self language. However, blind people still need assistance from sighted persons to be directed to the scale’s platform. The developed device has great potential as a low vision health aid for Self speakers. Moreover, the features of this device can be further improved by integrating iBeacon technology to increase the autonomy of blind people to use the scale and navigate to the device’s location safely.

IBeacon Indoor Positioning Method Combined with Real-Time Anomaly Rate to Determine Weight Matrix.

This paper proposes an indoor positioning method based on iBeacon technology that combines anomaly detection and a weighted Levenberg-Marquadt (LM) algorithm. The proposed solution uses the isolation forest algorithm for anomaly detection on the collected Received Signal Strength Indicator (RSSI) data from different iBeacon base stations, and calculates the anomaly rate of each signal source while eliminating abnormal signals. Then, a weight matrix is set by using each anomaly ratio and the RSSI value after eliminating the abnormal signal. Finally, the constructed weight matrix and the weighted LM algorithm are combined to solve the positioning coordinates. An Android smartphone was used to verify the positioning method proposed in this paper in an indoor scene. This experimental scenario revealed an average positioning error of 1.540 m and a root mean square error (RMSE) of 1.748 m. A large majority (85.71%) of the positioning point errors were less than 3 m. Furthermore, the RMSE of the method proposed in this paper was, respectively, 38.69%, 36.60%, and 29.52% lower than the RMSE of three other methods used for comparison. The experimental results show that the iBeacon-based indoor positioning method proposed in this paper can improve the precision of indoor positioning and has strong practicability.

Performance Evaluation of iBeacon Deployment for Location-Based Services in Physical Learning Spaces

Bluetooth Low Energy (BLE) is a wireless network technology used for transmitting data over short distances. BLE maintains a data transmission range comparable to the regular Bluetooth transmission, but consumes less energy and cost. iBeacon technology refers to BLE mobile devices, which allow mobile applications to receive signals from iBeacons in both indoor and outdoor environments. It is commonly used nowadays for positioning, location services, navigation and marketing, for the sustainable development of smart cities. The applications, however, can be further enhanced for use in many disciplines, such as education, health sector, and exhibitions for disseminating information. This study performed a set of robustness and performance tests on BLE-based iBeacons in the teaching and learning environments to evaluate the performance of iBeacon signals for positioning. During robustness testing, positioning accuracy, signal availability and stability were assessed under different environmental conditions, and the findings suggested pedestrian traffic blocking the line of sight between iBeacon and receiver, causing the most signal attenuations and variation in RSSI. In performance testing, a series of tests was conducted to evaluate the deployment of the iBeacons for positioning; leading to recommendations of iBeacon deployment location, density, transmission interval, fingerprint space interval and collection time in physical learning spaces for sustainable eLearning environments.

Application of Ibeacon in Indoor Positioning and Navigation

In recent years, with the development of new energy vehicles, the demand for indoor charging is increasing. In the construction and application development of large indoor parking lot, users’ demand for location-based service is more urgent. At this point the indoor positioning technology appears to be very important. At present, indoor mainstream technologies include UWB, RFID, ZigBee, ultrasonic, inertial navigation, optical positioning, iBeacon, Wi-fi and geomagnetic, etc. Compared with other technologies, iBeacon technology has the advantages of low power consumption and strong compatibility. IBeacon positioning technology helps users find idle charging piles more quickly and conveniently. This paper will briefly introduce the application of iBeacon in indoor positioning and navigation and related algorithms.

Location of Underground Parking Lot Based on Bluetooth Ibeacon Technology

With the popularity of electric vehicles in China, how to guide the vehicle to the charging facility in the underground garage has become an urgent problem to be solved. Among them, the realization of real-time vehicle location is one of the keys. In this paper, the location fingerprint scheme based on iBeacon technology is adopted, and the improved k-proximity algorithm is combined to realize the positioning.

Interactive student response system with iBeacon and web-socket for flipped classroom learning

The paper proposes an interactive student response portfolio (ISREP) system with iBeacon and web-socket technology, which supports flipped-classroom learning activities in traditional classrooms. The design of the ISREP system aims at promote interactions in classroom learning (CL). It offers APPs and web-interface functions for students and teachers, respectively. Students’ APP can scan iBeacon devices in classrooms and then automatically upload their identification information to the cloud space. Consequently, students’ presence in classroom can be recorded automatically. Moreover, teachers employ another function the system provides to promote high interaction in classroom via displaying questions on the front screen in classroom. Meanwhile, it simultaneously pushes (multicasts) these questions to students’ smartphones via web-socket technology. Subsequently, students send their responses for questions to the cloud space by the APP. During answering questions, the system presents temporary histograms of students’ responses and counting-down statuses of a timer on the screen in classroom. A timer can be synchronized with students’ APP by the web-socket technology. This way can promote students’ interaction and interest and then students enjoy in quiz-like activities. Teachers can quickly get results of students’ responses. A quasi-experiment was conducted in flipped-CL activities of a university class utilizing the system. Observing experimental results, it was found that students, who receive the instruction with the system, improved their interaction, learning interest, learning attitude, and learning satisfaction. Moreover, the proposed system helps teachers quickly obtain students’ learning situation in classroom and then may adjust their instructional approaches or contents.

Research and Application of Locating Factors Based on iBeacon Technology

In view of the shortage of most current research results on the basis of iBeacon localization technology based on the ideal single static environment, the problems in positioning based on iBeacon technology are analyzed and summarized through a large number of experiments. The research problems include: the impact of the iBeacon parameter configuration on iBeacon positioning, including the effect of transmit power of the iBeacon, the configuration of the transmit interval , and the factory error of iBeacon device on the positioning of the iBeacon; iBeacon's power consuption factor analysis, including the impact of transmit power, transmission interval, temperature sensing interval, inductance interval on iBeacon power consumption; RSSI correction, including RSSI attenuation analysis and the use of window to correct the RSSI; mobile device adaptation, including the comparison of RSSI reception between different Android terminal, adaptation methods and cost. And give the solutions of part of the above problems, and achieve the campus positioning system.

Distributed and collaborative proactive tandem location tracking of vehicle products for warehouse operations

Dynamic location information of the product in warehouse is vital for many processes such as order picking and stock taking. In the vehicle warehouse, stored products are mass customized vehicles with wheels which means they move frequently and haphazardly during operations. The dynamic location information of the vehicles is neither known nor updated, which thus lead to excessive time was consumed in searching, checking and picking the vehicles in warehouse. To solve this problem, this paper first presents the proactive tracking system architecture using iBeacon technology and the conception of distributed gateways. A collaborative and distributed tandem tracking approach is then proposed to realize tracking efficiency including the accuracy and responsiveness. We combine the location information with the warehouse working procedures seamlessly by adopting location-based service trigger. Finally, a real-life industrial case study is provided to verify the feasibility and effectiveness.

ANALYSING THE POTENTIAL OF BLE TO SUPPORT DYNAMIC BROADCASTING SCENARIOS

In this paper, we present a novel approach for broadcasting information based on a Bluetooth Low Energy (BLE) ibeacon technology. We propose a dynamic method that uses a combination of Wi-Fi and BLE technology where every technology plays a part in a user discovery and broadcasting process. In such system, a specific ibeacon device broadcasts the information when a user is in proximity. Using experiments, we conduct a scenario where the system discovers users, disseminates information, and later we use collected data to examine the system performance and capability. The results show that our proposed approach has a promising potential to become a powerful tool in the discovery and broadcasting concept that can be easily implemented and used in business environments.

Analysing the Potential of BLE to Support Dynamic Broadcasting Scenarios

In this paper, we present a novel approach for broadcasting information based on a Bluetooth Low Energy (BLE) ibeacon technology. We propose a dynamic method that uses a combination of Wi-Fi and BLE technology where every technology plays a part in a user discovery and broadcasting process. In such system, a specific ibeacon device broadcasts the information when a user is in proximity. Using experiments, we conduct a scenario where the system discovers users, disseminates information, and later we use collected data to examine the system performance and capability. The results show that our proposed approach has a promising potential to become a powerful tool in the discovery and broadcasting concept that can be easily implemented and used in business environments.

Three-Dimensional Modeling and Indoor Positioning for Urban Emergency Response

Three-dimensional modeling of building environments and indoor positioning is essential for emergency response in cities. Traditional ground-based measurement methods, such as geodetic astronomy, total stations, and global positioning system (GPS) receivers, cannot meet the demand for high precision positioning and it is therefore essential to conduct multiple-angle data-acquisition and establish three-dimensional spatial models. In this paper, a rapid modeling technology is introduced, which includes multiple-angle remote sensing image acquisition based on unmanned aerial vehicles (UAVs), an algorithm to remove linear and planar foregrounds before reconstructing the backgrounds, and a three-dimensional modeling (3DM) framework. Additionally, an indoor 3DM technology is introduced based on building design drawings, and an indoor positioning technology is developed using iBeacon technology. Finally, a prototype system of the indoor and outdoor positioning-service system in an urban firefighting rescue scenario is introduced to demonstrate the value of the method proposed in this paper.

Informal learning in science museum: development and evaluation of a mobile exhibit label system with iBeacon technology

Informal science learning has drawn the attention of researchers, educators and museum administrators for a long time. However, the problem of how to better support visitors to be more engaged while visiting exhibits and improve informal science learning performance is still missing. Context-aware technologies have the advantages of fostering learning interest and providing real time feedback. Previous studies have examined the effectiveness of 5E Learning Cycle in science learning. To address the problem, this study aims to develop a mobile label assisted system using the 5E Learning Cycle approach based on iBeacon technology in a science museum. A total of 43 college students participated in this study. Participants from different majors were assigned to two groups in an effort to make the groups relatively equivalent in terms of student majors. One group was the experimental group (mobile label assisted visiting mode, n = 21), and the other one was the control group (traditional visiting mode, n = 22). From the results of learning performance, stay-time, behavioral pattern analysis, and interviews, it was found that the mobile label assisted system can effectively guide visitors to interact with exhibits, conduct thoughtful learning, and prolong the visiting stay-time. Visitors are willing to visit the science museum with it. This was one of the very few studies focusing on the application of iBeacon to design mobile label system in a science museum. It turned out that iBeacon technology has huge potential applications for the future science museum.

Connecting people with their communities through proximity‐based digital storytelling

ABSTRACTThis visual presentation describes the results of a library‐led initiative involving the use of iBeacon proximity‐based technologies to connect people with their communities. The two libraries involved in this initiative developed and tested an app that pushed community‐based digital stories to users' smartphones and tablets when users were physically near a historic or cultural object (e.g., statue, landmark) about which the digital story was based. Using proximity‐based technologies to deliver stories about cultural and historic objects of interest to a community was thought to be a novel and engaging way to rally emotional connection and pride in one's own community. To test this hypothesis, as well as the viability of using iBeacon technology as a storytelling delivery mechanism, a pilot study was conducted with 50 participants from the general public at the two libraries involved in the initiative. Participants used the app to browse and read stories pertaining to a prominent park in the city. Posters with pictures of historic or cultural objects within the park were installed throughout each library. Each poster was enabled with iBeacon technology so that digital stories about the historic or cultural object displayed on the poster were automatically pushed to participants' smart devices as participants became near. To collect data on users' experiences and satisfaction with the app and the digital stories, on‐the‐spot interviews were conducted with participants after they finished visiting the posters and reading the digital stories. Interview data were analyzed using content data analysis techniques. A Likert‐scaled questionnaire was also administered; this data was analyzed using factor analysis and hierarchical regression. Results suggest that proximity‐based digital storytelling is a viable approach to connect people with their communities, especially if the stories provide people with relevant, timely, location‐based community information that stirs a positive emotional response.

Analysis of Object Location Accuracy for iBeacon Technology based on the RSSI Path Loss Model and Fingerprint Map

Abstract This paper presents analysis of object location accuracy of a mobile device on the basis of the iBeacon technology. The research starts with radio signal strength indicator analysis along the corridor in order to create a path loss model for iBeacon. Two cases are taken into account: line of sight and non-line of sight for model creation. For both cases two tests: Chi-square, Shapiro-Wilk have been performed. It has also been checked if the HCI (Host Controller Interface) is a source with a memory. Acquired data have been filtered with different type of filters, e.g. median, moving average and then compared. Next, the authors evaluated the indoor positioning trilateration algorithms with the use of created model for exemplary hall. The RSSI map (radiomap) was created and the logarithm propagation model was designed. The logarithmic model estimated distance with average error 1.09m for 1 – 9m and 1.75m for 1-20m and after trilateration, the positions with average error 2.45m was achieved. A statistical analysis for acquiring data led to the final conclusion which enhanced knowledge about positioning based on the popular iBeacon technology.

BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service.

The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption.

Discovering Co-Located Walking Groups of People Using iBeacon Technology

Co-located mobile users have found several useful and real-world applications in proximity-based services. Aiming at unleashing the potential of these proximity-based services, it is essential to devise robust techniques enabling smart devices to know their proximity close neighbors and be able to communicate with each other. To this end, we propose, design, and evaluate a robust framework capable to successfully co-localize walking groups of mobile users, in real-time and in a centralized manner. It leverages Bluetooth low energy technology to achieve a high degree of co-location accuracy. From the collected radio signals, we construct a graph network in which the distance between pairwise vertices represents the connection strength between mobile users. Then, we propose a modified version of edge betweenness techniques, with an average path length, as a key enabler for a high clustering accuracy. We analyze the performance in terms of clustering accuracy of the proposed scheme. First, we assess its performance numerically. Then, we conduct analysis on the experimental data set to demonstrate the feasibility and the efficiency of our method. Through obtained results, we have shown that our method can be successfully applied to co-localize people walking as part of the same group.

A mobile indoor positioning system based on iBeacon technology.

To increase the efficiency in the emergency room, the goal of this research is to implement a mobile-based indoor positioning system using mobile applications (APP) with the iBeacon solution based on the Bluetooth Low Energy (BLE) technology. We use the Received Signal Strength (RSS) based localization method to estimate the patients' locations. Our positioning algorithm achieves 97.22% (95% Confidence Interval = 95.90% - 98.55%) accuracy of classification. As the result, our mechanism is reliable enough to satisfy the need for medical staff to track the locations of their patients.