Sensor Localization System for AR-assisted Disaster Relief Applications (poster)

Choi, Hong-Beom; Lim, Kyung Soo; Ko, Young-Bae

doi:10.1145/3307334.3328607

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…Among the most favorable localization technologies other than UWB, wireless networks such as Wi-Fi [20][21][22][23], ZigBee [24], Bluetooth low energy (BLE) [25,26] and Message Queuing Telemetry Transport (MQTT) [15] are currently being used as they are easily accessible in most environments and are common in any modern hardware. These methods rely on RSS values from nearby Wi-Fi, ZigBee, and BLE that are measured by the mobile device at a specific location estimator, which then, through several steps, sends information to the second location estimator to determine the final location.…”

Section: Literature Reviewmentioning

confidence: 99%

Indoor Positioning System Based on UWB Rapid Integration with Unity Cross Platform Development Engine through IoT

Zikrul Hakiem Ishak,

Sallehuddin Mohamed Haris

2023

JAIT

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The changes in time have made divergences of endless possibilities in localization technology. Localization in an indoor environment is surely a concerning matter as several shortcomings always arise when dealing with indoor localization. To optimize localization in an indoor environment, tracking a subject’s position in real-time is a certainly vital interest. Challenges in obtaining an accurate position in precise millimetre accuracy whilst the subject perceive visual information rendered in real-time is somewhat always a matter in hand to address in an indoor environment. The main objective of this research is to implement a positioning method in an indoor environment base on ultra-wideband (UWB) technology to obtain position accuracy in millimetres by rapidly integrating with Unity three-dimensional (3D) engine hence obtaining a detailed inertial measurement unit (IMU) data via wireless Message Queuing Telemetry Transport (MQTT) network protocol. The key results of this research should ensure an establishment of an indoor positioning system based on providing the finest selection of positioning and UWB parameters. These fine selections are an important design choice impacting the system’s performance in obtaining an accurate position within the range of 0.15mm to 115mm. The technological benefits involve the innovation of wireless communication based on the internet of things (IoT) concept relevant to the Industrial Revolution 4.0 (IR 4.0) enabling participants to move freely in an indoor environment whilst obtaining accurate and precise positioning coordinates. Future recommendations comprise of real-time two-dimensional (2D) Pozyx Creator Controller integrated with Unity 3D user graphical user interface (GUI) purposes intended for mobile mapping navigations.

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Section: Literature Reviewmentioning

confidence: 99%

Indoor Positioning System Based on UWB Rapid Integration with Unity Cross Platform Development Engine through IoT

Zikrul Hakiem Ishak,

Sallehuddin Mohamed Haris

2023

JAIT

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“…In terms of encouraging and promoting innovation and modernization in education through mobile and information technology (IT), it also supports traditional lecture-style teaching, convenient information gathering, and information sharing and promotes innovative teaching methods such as cooperative learning [25,26], exploratory learning outside the classroom, and game-based learning [27]. On the flip side, the marvelous expansion of sensor technology in smartphone(s), along with their sensing capabilities for accurate capturing, monitoring, and analysis of information, helps us know about traffic conditions [28][29][30], road conditions [31][32][33], environmental impacts of noise level [34], air quality and pollution level [35][36][37][38][39], humidity and temperature [40], understand patterns of objects movements [41][42][43], alerting and monitoring disaster [44,45], weather information [46], etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Towards a Low-Cost Teacher Orchestration Using Ubiquitous Computing Devices for Detecting Student’s Engagement

Ahmad

Khusro

Alam

et al. 2022

Wireless Communications and Mobile Computing

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The ubiquitous devices and technologies to support teachers and students in a learning environment include the Internet of things (IoT), learning analytics (LA), augmented or virtual reality (AR/VR), ubiquitous learning environment (ULE), and wearables. However, most of these solutions are obtrusive, with substantial infrastructure costs and pseudo-real-time results. Real-time detection of students’ activeness, participation, and activity monitoring is important, especially during a pandemic. This research study provides a low-cost teacher orchestration solution with real-time results using off-the-shelf devices. The proposed solution determines a teacher’s activeness using multimodal data (MMD) from both teacher and student’s devices. The MMD extracts different features from data, decodes them, and displays them to the instructor in real time. It allows the instructor to update their teaching methodology in real time to get more students on board and provide a more engaging learning experience. Our experimental results show that real-time feedback about the classroom’s current status helped improve learning outcomes by about 45%. Also, we investigated a 50% increase in classroom engaging experience.

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“…UWB technology has significant advantages in localization owing to its centimeter-level ranging capability, multipath robustness, and low energy consumption [4,5]. UWB is considered as the most promising technology for accurate positioning, which is required for various applications such as the Internet of Things (IoT), wearable devices, extended reality (XR), sports training, maritime communication, future wireless networking, and unmanned aerial robots [6][7][8][9][10][11][12][13]. For example, in XR applications, if an object's location is incorrectly displayed, the user experience (UX) is significantly degraded.…”

Section: Introductionmentioning

confidence: 99%

Improving Deep Learning-Based UWB LOS/NLOS Identification with Transfer Learning: An Empirical Approach

et al. 2020

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This paper presents an improved ultra-wideband (UWB) line of sight (LOS)/non-line of sight (NLOS) identification scheme based on a hybrid method of deep learning and transfer learning. Previous studies have limitations, in that the classification accuracy significantly decreases in an unknown place. To solve this problem, we propose a transfer learning-based NLOS identification method for classifying the NLOS conditions of the UWB signal in an unmeasured environment. Both the multilayer perceptron and convolutional neural network (CNN) are introduced as classifiers for NLOS conditions. We evaluate the proposed scheme by conducting experiments in both measured and unmeasured environments. Channel data were measured using a Decawave EVK1000 in two similar indoor office environments. In the unmeasured environment, the existing CNN method showed an accuracy of approximately 44%, but when the proposed scheme was applied to the CNN, it showed an accuracy of up to 98%. The training time of the proposed scheme was measured to be approximately 48 times faster than that of the existing CNN. When comparing the proposed scheme with learning a new CNN in an unmeasured environment, the proposed scheme demonstrated an approximately 10% higher accuracy and approximately five times faster training time.

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Sensor Localization System for AR-assisted Disaster Relief Applications (poster)

Cited by 5 publications

References 5 publications

Indoor Positioning System Based on UWB Rapid Integration with Unity Cross Platform Development Engine through IoT

Indoor Positioning System Based on UWB Rapid Integration with Unity Cross Platform Development Engine through IoT

Towards a Low-Cost Teacher Orchestration Using Ubiquitous Computing Devices for Detecting Student’s Engagement

Improving Deep Learning-Based UWB LOS/NLOS Identification with Transfer Learning: An Empirical Approach

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