SiFi

2021 ◽  
Vol 2 (3) ◽  
pp. 1-21
Author(s):  
Deke Guo ◽  
Xiaoqiang Teng ◽  
Yulan Guo ◽  
Xiaolei Zhou ◽  
Zhong Liu
Keyword(s):  
Rapid Development ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Location Based Services ◽  
Shopping Mall ◽  
Inference Problem ◽  
Indoor Location ◽  
Label Semantics ◽  
Geometrical Constraints ◽  
Indoor Scenes

Due to the rapid development of indoor location-based services, automatically deriving an indoor semantic floorplan becomes a highly promising technique for ubiquitous applications. To make an indoor semantic floorplan fully practical, it is essential to handle the dynamics of semantic information. Despite several methods proposed for automatic construction and semantic labeling of indoor floorplans, this problem has not been well studied and remains open. In this article, we present a system called SiFi to provide accurate and automatic self-updating service. It updates semantics with instant videos acquired by mobile devices in indoor scenes. First, a crowdsourced-based task model is designed to attract users to contribute semantic-rich videos. Second, we use the maximum likelihood estimation method to solve the text inferring problem as the sequential relationship of texts provides additional geometrical constraints. Finally, we formulate the semantic update as an inference problem to accurately label semantics at correct locations on the indoor floorplans. Extensive experiments have been conducted across 9 weeks in a shopping mall with more than 250 stores. Experimental results show that SiFi achieves 84.5% accuracy of semantic update.

scholarly journals A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 875 ◽  
Author(s):  
Xiaochao Dang ◽  
Xiong Si ◽  
Zhanjun Hao ◽  
Yaning Huang
Keyword(s):  
Indoor Localization ◽  
Rapid Development ◽  
Location Based Services ◽  
Signal Interference ◽  
Indoor Environments ◽  
Phase Information ◽  
Localization Accuracy ◽  
Localization Method ◽  
Indoor Location ◽  
Conference Room

With the rapid development of wireless network technology, wireless passive indoor localization has become an increasingly important technique that is widely used in indoor location-based services. Channel state information (CSI) can provide more detailed and specific subcarrier information, which has gained the attention of researchers and has become an emphasis in indoor localization technology. However, existing research has generally adopted amplitude information for eigenvalue calculations. There are few research studies that have used phase information from CSI signals for localization purposes. To eliminate the signal interference existing in indoor environments, we present a passive human indoor localization method named FapFi, which fuses CSI amplitude and phase information to fully utilize richer signal characteristics to find location. In the offline stage, we filter out redundant values and outliers in the CSI amplitude information and then process the CSI phase information. A fusion method is utilized to store the processed amplitude and phase information as a fingerprint database. The experimental data from two typical laboratory and conference room environments were gathered and analyzed. The extensive experimental results demonstrate that the proposed algorithm is more efficient than other algorithms in data processing and achieves decimeter-level localization accuracy.

scholarly journals WiFi FTM, UWB and Cellular-Based Radio Fusion for Indoor Positioning

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7020
Author(s):  
Carlos S. Álvarez-Merino ◽  
Hao Qiang Luo-Chen ◽  
Emil Jatib Khatib ◽  
Raquel Barco
Keyword(s):  
High Precision ◽  
Likelihood Estimation ◽  
Wide Band ◽  
Reference Points ◽  
Location Based Services ◽  
Coverage Area ◽  
Location Services ◽  
Indoor Location ◽  
Location Service ◽  
Indoor Localisation

High-precision indoor localisation is becoming a necessity with novel location-based services that are emerging around 5G. The deployment of high-precision indoor location technologies is usually costly due to the high density of reference points. In this work, we propose the opportunistic fusion of several different technologies, such as ultra-wide band (UWB) and Wi-Fi fine-time measurement (FTM), in order to improve the performance of location. We also propose the use of fusion with cellular networks, such as LTE, to complement these technologies where the number of reference points is under-determined, increasing the availability of the location service. Maximum likelihood estimation (MLE) is presented to weight the different reference points to eliminate outliers, and several searching methods are presented and evaluated for the localisation algorithm. An experimental setup is used to validate the presented system, using UWB and Wi-Fi FTM due to their incorporation in the latest flagship smartphones. It is shown that the use of multi-technology fusion in trilateration algorithm remarkably optimises the precise coverage area. In addition, it reduces the positioning error by over-determining the positioning problem. This technique reduces the costs of any network deployment oriented to location services, since a reduced number of reference points from each technology is required.

scholarly journals Ephemeral ID Beacon-Based Improved Indoor Positioning System

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 622 ◽  
Author(s):  
Jinsu Kang ◽  
Jeonghoon Seo ◽  
Yoojae Won
Keyword(s):  
Tracking System ◽  
Rapid Development ◽  
Communication Technologies ◽  
Location Based Services ◽  
Received Signal Strength Indicator ◽  
Indoor Location ◽  
Indoor Space ◽  
Outdoor Spaces ◽  
Physical Barriers ◽  
Positioning Algorithm

Recently, the rapid development of mobile devices and communication technologies has dramatically increased the demand for location-based services that provide users with location-oriented information and services. User location in outdoor spaces is measured with high accuracy using GPS. However, because the indoor reception of GPS signals is not smooth, this solution is not viable in indoor spaces. Many on-going studies are exploring new approaches for indoor location measurement. One popular technique involves using the received signal strength indicator (RSSI) values from the Bluetooth Low Energy (BLE) beacons to measure the distance between a mobile device and the beacons and then determining the position of the user in an indoor space by applying a positioning algorithm such as the trilateration method. However, it remains difficult to obtain accurate data because RSSI values are unstable owing to the influence of elements in the surrounding environment such as weather, humidity, physical barriers, and interference from other signals. In this paper, we propose an indoor location tracking system that improves performance by correcting unstable RSSI signals received from BLE beacons. We apply a filter algorithm based on the average filter and the Kalman filter to reduce the error range of results calculated using the RSSI values.

Indoor Location Tracking Using Time of Arrival Estimation Method

2020 ◽  
Vol 10 (2) ◽  
pp. 290-297
Author(s):  
Nandita Sreekumar ◽  
Shoney Sebastian
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Node ◽  
Estimation Method ◽  
Location Based Services ◽  
Wireless Sensor ◽  
Time Of Arrival ◽  
Location Tracking ◽  
Indoor Location ◽  
Mobile Sensor Node ◽  
Common Application

Background & Objective: Location-based services enable collection of location-oriented information which finds use in various fields. Methods: With its utility found in so many applications, various localization techniques are adopted to improve these services. One such property of a signal which is used for these estimations is known as ‘Time of Arrival’ property. The ‘Time of Arrival’ property of a signal is the time difference for a signal to go from the transmitter to the receiver. The most common application is to navigate through places, finding or tracking your personal belongings, targeted advertisements by knowing the nearby popular places and various other services like augmented reality gaming among others. Results & Conclusion: Through this paper, we demonstrate a method to track the location of a mobile sensor node using Trilateration algorithm with the help of Time of Arrival (ToA) property of signals. The time of arrival of packets at each node is recorded and data collected from the simulation of a wireless sensor network for this experiment is spread across various distributions to find the optimum statistical inference.

Geometry-Aided BLE-Based Smartphone Positioning for Indoor Location-Based Services

2020 ◽  
Author(s):  
Branislav Rudic ◽  
Maria Anneliese Klaffenbock ◽  
Markus Pichler-Scheder ◽  
Dmitry Efrosinin ◽  
Christian Kastl
Keyword(s):  
Location Based Services ◽  
Indoor Location

Institutional Quality and Trade Flow: Empirical Evidence from Malaysia and Other OIC Member Countries in Africa

2021 ◽  
pp. 097508782098717
Author(s):  
Hammed Agboola Yusuf ◽  
Luqman Olanrewaju Afolabi ◽  
Waliu Olawale Shittu ◽  
Kafilah Lola Gold ◽  
Murtala Muhammad
Keyword(s):  
Economic Growth ◽  
Bilateral Trade ◽  
Trade Flow ◽  
Estimation Method ◽  
Institutional Quality ◽  
Likelihood Estimation ◽  
Political Stability ◽  
Bilateral Trade Flow ◽  
World Governance Indicators ◽  
The Impact

This article examines the impact of institutional quality on bilateral trade flow between Malaysia and selected 25 African Organisation of Islamic Cooperation (OIC) member countries. Four institutional qualities were selected from World Governance Indicators with other trade predictors from the period from 1985 to 2016. Using gravity model of trade and Poisson pseudo-maximum likelihood estimation method (PPML) technique, the results confirm that government effectiveness, regulatory quality and political stability have an adverse effect on bilateral trade flow among the OIC countries in Africa. On the other hand, these institutional quality variables were considered as a strength for Malaysian economic growth. Therefore, better institutional quality reforms are needed among OIC member countries in Africa in order to accelerate trade, economic growth and development in their region.

scholarly journals A multi-group higher-order factor analysis for studying the gender-effect in Teacher Job Satisfaction

METRON ◽  
2021 ◽  
Author(s):  
Carlo Cavicchia ◽  
Pasquale Sarnacchiaro
Keyword(s):  
Job Satisfaction ◽  
Factor Analysis ◽  
Secondary School Teachers ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Higher Order ◽  
Teacher Job Satisfaction ◽  
Public Secondary School ◽  
Order Factor ◽  
Maximum Likelihood Estimation Method

AbstractTeachers’ performances also depend on whether and how they are satisfied with their job. Therefore, Teacher Job Satisfaction must be considered as the driver of teachers’ accomplishments. To plan future policies and improve the overall teaching process, it is crucial to understand which factors mostly contribute to Teacher Job Satisfaction. A Common Assessment Framework and Education questionnaire was administered to 163 Italian public secondary school teachers to collect data, and a second-order factor analysis was used to detect which factors impact on Teacher Job Satisfaction, and to what extent. This model-based approach guarantees to detect factors which respect important properties: unidimensionality and reliability. All the coefficients are estimated according to the maximum likelihood estimation method in order to make inference on the parameters and on the validity of the model. Moreover, a new multi-group test for higher-order factor analysis was proposed and implemented. Finally, we analyzed in detail whether the factors impacting Teacher Job Satisfaction are characterized by gender.

scholarly journals Calibration Analysis of High-G MEMS Accelerometer Sensor Based on Wavelet and Wavelet Packet Denoising

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1231
Author(s):  
Yunbo Shi ◽  
Juanjuan Zhang ◽  
Jingjing Jiao ◽  
Rui Zhao ◽  
Huiliang Cao
Keyword(s):  
Wavelet Packet ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Parameter Extraction ◽  
Accelerometer Sensor ◽  
Oscillation Phase ◽  
Mems Accelerometer ◽  
Optimal Tree ◽  
Adaptive Decomposition ◽  
Entropy Criterion

High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.

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.

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