scholarly journals Calibration of Wi-Fi-Based Indoor Tracking Systems for Android-Based Smartphones

2019 ◽  
Vol 11 (9) ◽  
pp. 1072 ◽  
Author(s):  
Miguel Martínez del Horno ◽  
Ismael García-Varea ◽  
Luis Orozco Barbosa
Keyword(s):  
Indoor Localization ◽  
Tracking System ◽  
Signal Propagation ◽  
Tracking Systems ◽  
Tracking Accuracy ◽  
Indoor Location ◽  
Static Calibration ◽  
Open Issue ◽  
Indoor Tracking ◽  
Indoor Location Systems

With the growing development of smartphones equipped with Wi-Fi technology and the need of inexpensive indoor location systems, many researchers are focusing their efforts on the development of Wi-Fi-based indoor localization methods. However, due to the difficulties in characterizing the Wi-Fi radio signal propagation in such environments, the development of universal indoor localization mechanisms is still an open issue. In this paper, we focus on the calibration of Wi-Fi-based indoor tracking systems to be used by smartphones. The primary goal is to build an accurate and robust Wi-Fi signal propagation representation in indoor scenarios.We analyze the suitability of our approach in a smartphone-based indoor tracking system by introducing a novel in-motion calibration methodology using three different signal propagation characterizations supplemented with a particle filter. We compare the results obtained with each one of the three characterization in-motion calibration methodologies and those obtained using a static calibration approach, in a real-world scenario. Based on our experimental results, we show that the use of an in-motion calibration mechanism considerably improves the tracking accuracy.

scholarly journals COMBINING INDEPENDENT VISUALIZATION AND TRACKING SYSTEMS FOR AUGMENTED REALITY

2018 ◽  
Vol XLII-2 ◽  
pp. 455-462
Author(s):  
P. Hübner ◽  
M. Weinmann ◽  
M. Hillemann ◽  
B. Jutzi ◽  
S. Wursthorn
Keyword(s):  
Augmented Reality ◽  
Tracking System ◽  
Tracking Systems ◽  
Tracking Accuracy ◽  
Visualization System ◽  
System A ◽  
Augmented Reality Application ◽  
Relative Pose ◽  
Inside Out ◽  
Visualization Device

The basic requirement for the successful deployment of a mobile augmented reality application is a reliable tracking system with high accuracy. Recently, a helmet-based inside-out tracking system which meets this demand has been proposed for self-localization in buildings. To realize an augmented reality application based on this tracking system, a display has to be added for visualization purposes. Therefore, the relative pose of this visualization platform with respect to the helmet has to be tracked. In the case of hand-held visualization platforms like smartphones or tablets, this can be achieved by means of image-based tracking methods like marker-based or model-based tracking. In this paper, we present two marker-based methods for tracking the relative pose between the helmet-based tracking system and a tablet-based visualization system. Both methods were implemented and comparatively evaluated in terms of tracking accuracy. Our results show that mobile inside-out tracking systems without integrated displays can easily be supplemented with a hand-held tablet as visualization device for augmented reality purposes.

A Comparison of the Accuracy of an Electromagnetic and a Hybrid Ultrasound-Inertia Position Tracking System

2001 ◽  
Vol 10 (6) ◽  
pp. 657-663 ◽  
Author(s):  
Volodymyr Kindratenko
Keyword(s):  
Tracking System ◽  
Position Tracking ◽  
Location Tracking ◽  
Comparison Study ◽  
Tracking Systems ◽  
Tracking Accuracy ◽  
Wide Range ◽  
Cave Environment ◽  
The Impact

Results of a comparison study of the tracking accuracy of two commercially available wide-range position tracking systems suitable for CAVEs are presented. An experiment was conducted with Flock of Birds and IS-900 tracking systems installed in the same CAVE environment to compare their accuracy. Another experiment was performed with a newly deployed IS-900 to investigate the impact of different ultrasound emitter configurations on the accuracy of the location tracking. The results show that the IS-900 has a much better accuracy over a larger range of operation than does the Flock of Birds; however, it is sensitive to the optimality of the ultrasound emitters configuration.

GPS and GSM Based Tracking System for Objects Moving over Wide Geographical Areas

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Fatima Ameen ◽  
Ziad Mohammed ◽  
Abdulrahman Siddiq
Keyword(s):  
Global Positioning System ◽  
Mobile Communications ◽  
Moving Objects ◽  
Tracking System ◽  
Geographical Area ◽  
Tracking Systems ◽  
Acceptable Result ◽  
Internet Service ◽  
Global Positioning ◽  
Tracking Objects

Tracking systems of moving objects provide a useful means to better control, manage and secure them. Tracking systems are used in different scales of applications such as indoors, outdoors and even used to track vehicles, ships and air planes moving over the globe. This paper presents the design and implementation of a system for tracking objects moving over a wide geographical area. The system depends on the Global Positioning System (GPS) and Global System for Mobile Communications (GSM) technologies without requiring the Internet service. The implemented system uses the freely available GPS service to determine the position of the moving objects. The tests of the implemented system in different regions and conditions show that the maximum uncertainty in the obtained positions is a circle with radius of about 16 m, which is an acceptable result for tracking the movement of objects in wide and open environments.

scholarly journals Privacy vs. Reward in Indoor Location-Based Services

2016 ◽  
Vol 2016 (4) ◽  
pp. 102-122 ◽  
Author(s):  
Kassem Fawaz ◽  
Kyu-Han Kim ◽  
Kang G. Shin
Keyword(s):  
Location Privacy ◽  
Indoor Localization ◽  
Service Providers ◽  
Location Based Services ◽  
Location Information ◽  
Privacy Concerns ◽  
Indoor Location ◽  
Location Data ◽  
Personalized Services ◽  
Privacy Risks

AbstractWith the advance of indoor localization technology, indoor location-based services (ILBS) are gaining popularity. They, however, accompany privacy concerns. ILBS providers track the users’ mobility to learn more about their behavior, and then provide them with improved and personalized services. Our survey of 200 individuals highlighted their concerns about this tracking for potential leakage of their personal/private traits, but also showed their willingness to accept reduced tracking for improved service. In this paper, we propose PR-LBS (Privacy vs. Reward for Location-Based Service), a system that addresses these seemingly conflicting requirements by balancing the users’ privacy concerns and the benefits of sharing location information in indoor location tracking environments. PR-LBS relies on a novel location-privacy criterion to quantify the privacy risks pertaining to sharing indoor location information. It also employs a repeated play model to ensure that the received service is proportionate to the privacy risk. We implement and evaluate PR-LBS extensively with various real-world user mobility traces. Results show that PR-LBS has low overhead, protects the users’ privacy, and makes a good tradeoff between the quality of service for the users and the utility of shared location data for service providers.

Deep learning approach for UHF RFID-based indoor localization

2021 ◽  
pp. 1-13
Author(s):  
Haishu Ma ◽  
Zongzheng Ma ◽  
Lixia Li ◽  
Ya Gao
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Estimation Error ◽  
Research Direction ◽  
Linear Interpolation ◽  
Linear Mapping ◽  
Uhf Rfid ◽  
Indoor Location ◽  
Main Research

Due to the proliferation of the IoT devices, indoor location-based service is bringing huge business values and potentials. The positioning accuracy is restricted by the variability and complexity of the indoor environment. Radio Frequency Identification (RFID), as a key technology of the Internet of Things, has became the main research direction in the field of indoor positioning because of its non-contact, non-line-of-sight and strong anti-interference abilities. This paper proposes the deep leaning approach for RFID based indoor localization. Since the measured Received Signal Strength Indicator (RSSI) can be influenced by many indoor environment factors, Kalman filter is applied to erase the fluctuation. Furthermore, linear interpolation is adopted to increase the density of the reference tags. In order to improve the processing ability of the fingerprint database, deep neural network is adopted together with the fingerprinting method to optimize the non-linear mapping between fingerprints and indoor coordinates. The experimental results show that the proposed method achieves high accuracy with a mean estimation error of 0.347 m.

scholarly journals High Precision Optical Tracking System Based on near Infrared Trinocular Stereo Vision

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2528
Author(s):  
Songlin Bi ◽  
Yonggang Gu ◽  
Jiaqi Zou ◽  
Lianpo Wang ◽  
Chao Zhai ◽  
...  
Keyword(s):  
High Precision ◽  
Stereo Vision ◽  
Near Infrared ◽  
Nearest Neighbor ◽  
Tracking System ◽  
Optical Tracking ◽  
Tracking Accuracy ◽  
Optical Tracking System ◽  
Dynamic Tracking ◽  
Trinocular Stereo

A high precision optical tracking system (OTS) based on near infrared (NIR) trinocular stereo vision (TSV) is presented in this paper. Compared with the traditional OTS on the basis of binocular stereo vision (BSV), hardware and software are improved. In the hardware aspect, a NIR TSV platform is built, and a new active tool is designed. Imaging markers of the tool are uniform and complete with large measurement angle (>60°). In the software aspect, the deployment of extra camera brings high computational complexity. To reduce the computational burden, a fast nearest neighbor feature point extraction algorithm (FNNF) is proposed. The proposed method increases the speed of feature points extraction by hundreds of times over the traditional pixel-by-pixel searching method. The modified NIR multi-camera calibration method and 3D reconstruction algorithm further improve the tracking accuracy. Experimental results show that the calibration accuracy of the NIR camera can reach 0.02%, positioning accuracy of markers can reach 0.0240 mm, and dynamic tracking accuracy can reach 0.0938 mm. OTS can be adopted in high-precision dynamic tracking.

scholarly journals Using Synthetic Data to Improve and Evaluate the Tracking Performance of Construction Workers on Site

2020 ◽  
Vol 10 (14) ◽  
pp. 4948
Author(s):  
Marcel Neuhausen ◽  
Patrick Herbers ◽  
Markus König
Keyword(s):  
Real World ◽  
Safety Management ◽  
Tracking System ◽  
Synthetic Data ◽  
Tracking Systems ◽  
Construction Sites ◽  
Virtual Construction ◽  
Percentage Points ◽  
Video Frames ◽  
Graphics Software

Vision-based tracking systems enable the optimization of the productivity and safety management on construction sites by monitoring the workers’ movements. However, training and evaluation of such a system requires a vast amount of data. Sufficient datasets rarely exist for this purpose. We investigate the use of synthetic data to overcome this issue. Using 3D computer graphics software, we model virtual construction site scenarios. These are rendered for the use as a synthetic dataset which augments a self-recorded real world dataset. Our approach is verified by means of a tracking system. For this, we train a YOLOv3 detector identifying pedestrian workers. Kalman filtering is applied to the detections to track them over consecutive video frames. First, the detector’s performance is examined when using synthetic data of various environmental conditions for training. Second, we compare the evaluation results of our tracking system on real world and synthetic scenarios. With an increase of about 7.5 percentage points in mean average precision, our findings show that a synthetic extension is beneficial for otherwise small datasets. The similarity of synthetic and real world results allow for the conclusion that 3D scenes are an alternative to evaluate vision-based tracking systems on hazardous scenes without exposing workers to risks.

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