scholarly journals Evolution of Indoor Positioning Technologies: A Survey

2017 ◽  
Vol 2017 ◽  
pp. 1-21 ◽  
Author(s):  
Ramon F. Brena ◽  
Juan Pablo García-Vázquez ◽  
Carlos E. Galván-Tejada ◽  
David Muñoz-Rodriguez ◽  
Cesar Vargas-Rosales ◽  
...  
Keyword(s):  
Classification Scheme ◽  
Communication Technologies ◽  
Indoor Positioning ◽  
Wide Field ◽  
Market Opportunity ◽  
Indoor Environments ◽  
Positioning Systems ◽  
Limited Perspective ◽  
Wide Range ◽  
Key Technologies

Indoor positioning systems (IPS) use sensors and communication technologies to locate objects in indoor environments. IPS are attracting scientific and enterprise interest because there is a big market opportunity for applying these technologies. There are many previous surveys on indoor positioning systems; however, most of them lack a solid classification scheme that would structurally map a wide field such as IPS, or omit several key technologies or have a limited perspective; finally, surveys rapidly become obsolete in an area as dynamic as IPS. The goal of this paper is to provide a technological perspective of indoor positioning systems, comprising a wide range of technologies and approaches. Further, we classify the existing approaches in a structure in order to guide the review and discussion of the different approaches. Finally, we present a comparison of indoor positioning approaches and present the evolution and trends that we foresee.

scholarly journals A Review on Indoor Positioning Technologies and its Principles

2021 ◽  
Vol 9 (VII) ◽  
pp. 494-501
Author(s):  
Pradyumna C
Keyword(s):  
Indoor Localization ◽  
Indoor Positioning ◽  
Line Of Sight ◽  
Indoor Environments ◽  
Daily Lives ◽  
Positioning Systems ◽  
Wide Range ◽  
Outdoor Environments ◽  
Location Detection ◽  
Pass Through

This paper aims to provide the reader with a review of the main technologies present in the literature to solve the indoor localization problem that is indoor positioning without GPS. Location detection has been implemented very successfully in outdoor environments using GPS technology. GPS has had a great impact on our daily lives by supporting a large number of applications. However, in indoor environments, the availability of GPS or equivalent satellite-based positioning systems is limited due to the lack of line of sight and attenuation of the GPS signal when they pass through walls. The goal of this paper is to provide a technical perspective on indoor positioning systems, including a wide range of technologies and methods.

Robustness in Fingerprinting-Based Indoor Positioning Systems

2018 ◽  
pp. 88-141 ◽  
Author(s):  
Shih-Hau Fang
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Signal Strength ◽  
Histogram Equalization ◽  
Indoor Positioning ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Location Based Services ◽  
Indoor Environments ◽  
Positioning Systems

Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. Received signal strength (RSS), mostly utilized in Wi-Fi fingerprinting systems, is known to be unreliable due to two reasons: orientation mismatch and variations in hardware. This chapter introduces an approach based on histogram equalization to compensate for orientation mismatch in robust Wi-Fi localization. The proposed method involves converting the temporal-spatial radio signal strength into a reference function (i.e., equalizing the histogram). This chapter also introduces an enhanced positioning feature, which is called delta-fused principal strength, to enhance the robustness of Wi-Fi localization against the problem of heterogeneous hardware. This algorithm computes the pairwise delta RSS and then integrates with RSS using principal component analysis. The proposed methods effectively and efficiently improve the robustness of location estimation in the presence of mismatch orientation and hardware variations, respectively.

scholarly journals An Infrastructure-Free Magnetic-Based Indoor Positioning System with Deep Learning

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6664
Author(s):  
Letícia Fernandes ◽  
Sara Santos ◽  
Marília Barandas ◽  
Duarte Folgado ◽  
Ricardo Leonardo ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Indoor Positioning ◽  
Test Dataset ◽  
Magnetic Field Data ◽  
Positioning Systems ◽  
Additional Information ◽  
Information Layer ◽  
Wide Range ◽  
Indoor Positioning System ◽  
New Infrastructure

Infrastructure-free Indoor Positioning Systems (IPS) are becoming popular due to their scalability and a wide range of applications. Such systems often rely on deployed Wi-Fi networks. However, their usability may be compromised, either due to scanning restrictions from recent Android versions or the proliferation of 5G technology. This raises the need for new infrastructure-free IPS independent of Wi-Fi networks. In this paper, we propose the use of magnetic field data for IPS, through Deep Neural Networks (DNN). Firstly, a dataset of human indoor trajectories was collected with different smartphones. Afterwards, a magnetic fingerprint was constructed and relevant features were extracted to train a DNN that returns a probability map of a user’s location. Finally, two postprocessing methods were applied to obtain the most probable location regions. We asserted the performance of our solution against a test dataset, which produced a Success Rate of around 80%. We believe that these results are competitive for an IPS based on a single sensing source. Moreover, the magnetic field can be used as an additional information layer to increase the robustness and redundancy of current multi-source IPS.

scholarly journals Indoor Positioning on Disparate Commercial Smartphones Using Wi-Fi Access Points Coverage Area

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4351 ◽  
Author(s):  
Ashraf ◽  
Hur ◽  
Park
Keyword(s):  
Human Mobility ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Indoor Environments ◽  
Coverage Area ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Access Points ◽  
Intersection Area ◽  
The Impact

The applications of location-based services require precise location information of a user both indoors and outdoors. Global positioning system’s reduced accuracy for indoor environments necessitated the initiation of Indoor Positioning Systems (IPSs). However, the development of an IPS which can determine the user’s position with heterogeneous smartphones in the same fashion is a challenging problem. The performance of Wi-Fi fingerprinting-based IPSs is degraded by many factors including shadowing, absorption, and interference caused by obstacles, human mobility, and body loss. Moreover, the use of various smartphones and different orientations of the very same smartphone can limit its positioning accuracy as well. As Wi-Fi fingerprinting is based on Received Signal Strength (RSS) vector, it is prone to dynamic intrinsic limitations of radio propagation, including changes over time, and far away locations having similar RSS vector. This article presents a Wi-Fi fingerprinting approach that exploits Wi-Fi Access Points (APs) coverage area and does not utilize the RSS vector. Using the concepts of APs coverage area uniqueness and coverage area overlap, the proposed approach calculates the user’s current position with the help of APs’ intersection area. The experimental results demonstrate that the device dependency can be mitigated by making the fingerprinting database with the proposed approach. The experiments performed at a public place proves that positioning accuracy can also be increased because the proposed approach performs well in dynamic environments with human mobility. The impact of human body loss is studied as well.

scholarly journals GEOFENCING-BASED LOCALIZATION FOR 3D DATA ACQUISITION NAVIGATION

2016 ◽  
Vol XLI-B4 ◽  
pp. 319-324
Author(s):  
M. Nakagawa ◽  
T. Kamio ◽  
H. Yasojima ◽  
T. Kobayashi
Keyword(s):  
Data Acquisition ◽  
Indoor Positioning ◽  
Outdoor Environment ◽  
Indoor Environments ◽  
Positioning Systems ◽  
3D Data ◽  
Localization And Mapping ◽  
Sensor Position ◽  
Position Data ◽  
Infrastructure Inspection

Users require navigation for many location-based applications using moving sensors, such as autonomous robot control, mapping route navigation and mobile infrastructure inspection. In indoor environments, indoor positioning systems using GNSSs can provide seamless indoor-outdoor positioning and navigation services. However, instabilities in sensor position data acquisition remain, because the indoor environment is more complex than the outdoor environment. On the other hand, simultaneous localization and mapping processing is better than indoor positioning for measurement accuracy and sensor cost. However, it is not easy to estimate position data from a single viewpoint directly. Based on these technical issues, we focus on geofencing techniques to improve position data acquisition. In this research, we propose a methodology to estimate more stable position or location data using unstable position data based on geofencing in indoor environments. We verify our methodology through experiments in indoor environments.

scholarly journals Multilateration Approach for Wide Range Visible Light Indoor Positioning System Using Mobile CMOS Image Sensor

2021 ◽  
Vol 11 (16) ◽  
pp. 7308
Author(s):  
Md Habibur Rahman ◽  
Mohammad Abrar Shakil Sejan ◽  
Wan-Young Chung
Keyword(s):  
Visible Light ◽  
Real Time ◽  
Indoor Positioning ◽  
Image Sensor ◽  
Computational Time ◽  
Positioning System ◽  
Horizontal Distance ◽  
Large Area ◽  
Positioning Systems ◽  
Wide Range

Visible light positioning (VLP) is a cost-effective solution to the increasing demand for real-time indoor positioning. However, owing to high computational costs and complicated image processing procedures, most of the existing VLP systems fail to deliver real-time positioning ability and better accuracy for image sensor-based large-area indoor environments. In this study, an effective method is proposed to receive coordinate information from multiple light-emitting diode (LED) lights simultaneously. It provides better accuracy in large experimental areas with many LEDs by using a smartphone-embedded image sensor as a terminal device and the existing LED lighting infrastructure. A flicker-free frequency shift on–off keying line coding modulation scheme was designed for the positioning system to ensure a constant modulated frequency. We tested the performance of the decoding accuracy with respect to vertical and horizontal distance, which utilizes a rolling shutter mechanism of a complementary metal-oxide-semiconductor image sensor. The experimental results of the proposed positioning system can provide centimeter-level accuracy with low computational time, rendering it a promising solution for the future direction of large-area indoor positioning systems.

scholarly journals GEOFENCING-BASED LOCALIZATION FOR 3D DATA ACQUISITION NAVIGATION

2016 ◽  
Vol XLI-B4 ◽  
pp. 319-324
Author(s):  
M. Nakagawa ◽  
T. Kamio ◽  
H. Yasojima ◽  
T. Kobayashi
Keyword(s):  
Data Acquisition ◽  
Indoor Positioning ◽  
Outdoor Environment ◽  
Indoor Environments ◽  
Positioning Systems ◽  
3D Data ◽  
Localization And Mapping ◽  
Sensor Position ◽  
Position Data ◽  
Infrastructure Inspection

Users require navigation for many location-based applications using moving sensors, such as autonomous robot control, mapping route navigation and mobile infrastructure inspection. In indoor environments, indoor positioning systems using GNSSs can provide seamless indoor-outdoor positioning and navigation services. However, instabilities in sensor position data acquisition remain, because the indoor environment is more complex than the outdoor environment. On the other hand, simultaneous localization and mapping processing is better than indoor positioning for measurement accuracy and sensor cost. However, it is not easy to estimate position data from a single viewpoint directly. Based on these technical issues, we focus on geofencing techniques to improve position data acquisition. In this research, we propose a methodology to estimate more stable position or location data using unstable position data based on geofencing in indoor environments. We verify our methodology through experiments in indoor environments.

Key Technologies for Indoor Positioning Systems

2019 ◽  
Author(s):  
Jullia Cristiana Romina BIRSAN ◽  
Florica Moldoveanu ◽  
Alin Moldoveanu ◽  
Maria-Iuliana Dascalu ◽  
Anca MORAR
Keyword(s):  
Indoor Positioning ◽  
Positioning Systems ◽  
Key Technologies

scholarly journals Indoor Positioning Algorithm Based on Maximum Correntropy Unscented Information Filter

2021 ◽  
Vol 10 (7) ◽  
pp. 441
Author(s):  
Li Ma ◽  
Ning Cao ◽  
Xiaoliang Feng ◽  
Minghe Mao
Keyword(s):  
Information Entropy ◽  
Gaussian Noise ◽  
Indoor Positioning ◽  
Indoor Environments ◽  
State Matrix ◽  
Positioning Systems ◽  
Information Filter ◽  
Non Gaussian ◽  
Positioning Algorithm ◽  
Information Vector

In view of the fact that indoor positioning systems are usually affected by non-Gaussian noise in complex indoor environments, this paper tests the data in the actual scene and analyzes the distribution characteristics of noise, and proposes a new indoor positioning algorithm based on maximum correntropy unscented information filter (MCUIF). The proposed indoor positioning algorithm includes three steps: First, the estimation of the state matrix and the corresponding covariance matrix are predicted through the unscented transformation (UT). Second, the observed information is reconstructed by using a nonlinear regression method on the basis of the maximum correntropy criterion (MCC). Third, the contribution of information vector is gained by non-Gaussian measurement and the predicted information vector is corrected by the contribution of information vector. Finally, the gain of information filtering is got by the information entropy state matrix and the information entropy measurement matrix to calculate the position coordinates of the unknown nodes. This algorithm enhances the robustness of the MCUIF to non-Gaussian noise in complex indoor environments. The results from the indoor positioning experiments show that MCUIF is better than the traditional methods in state estimation and position location of the unknown nodes.

scholarly journals A NEW UBIQUITOUS-BASED INDOOR POSITIONING SYSTEM WITH MINIMUM EXTRA HARDWARE USING SMART PHONES

2014 ◽  
Vol XL-2/W3 ◽  
pp. 151-155
Author(s):  
S. Hassany Pazoky ◽  
A. Chehreghan ◽  
A. Sadeghi Niaraki ◽  
R. Ali Abbaspour
Keyword(s):  
Smart Phone ◽  
Indoor Positioning ◽  
Smart Phones ◽  
Embedded Sensors ◽  
Indoor Environments ◽  
Step Counter ◽  
Positioning Systems ◽  
Acceptable Range ◽  
Technological Advances ◽  
Indoor Positioning System

Knowing the position has been an ambition in many areas such as science, military, business, etc. GPS was the realization of this wish in 1970s. Technological advances such as ubiquitous computing, as a conquering perspective, requires any service to work for any user, any place, anytime, and via any network. As GPS cannot provide services in indoor environments, many scientists began to develop indoor positioning systems (IPS). Smart phones penetrating our everyday lives were a great platform to host IPS applications. Sensors in smart phones were another big motive to develop IPS applications. Many researchers have been working on the topic developing various applications. However, the applications introduced lack simplicity. In other words, they need to install a step counter or smart phone on the ankle, which makes it awkward and inapplicable in many situations. In the current study, a new IPS methodology is introduced using only the usual embedded sensors in the smart phones. The robustness of this methodology cannot compete with those of the aforementioned approaches. The price paid for simplicity was decreasing robustness and complicating the methods and formulations. However, methods or tricks to harness the errors to an acceptable range are introduced as the future works.

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