Unsupervised Learning Based Acoustic NLOS Identification for Smart phone Indoor Positioning

2020 ◽  
Author(s):  
Wentao Xue ◽  
Zhixin Hu ◽  
Nan Wang ◽  
Lei Zhang
Keyword(s):  
Unsupervised Learning ◽  
Smart Phone ◽  
Indoor Positioning

scholarly journals IBPS: iBeacons Based Improved Indoor Positioning System

2020 ◽  
Vol 8 (5) ◽  
pp. 3792-3797
Keyword(s):  
Research Work ◽  
Energy Resource ◽  
Smart Phone ◽  
Indoor Positioning ◽  
Small Scale ◽  
Positioning System ◽  
Human Organ ◽  
Proposed Model ◽  
Small Hand ◽  
Indoor Positioning System

Smartphone plays a key role in integrating the entire world into a small hand. This feature made these smartphones as another human organ of many people. One of the main feature in every smart phone is GPS which used to travel new places, to locate and find optimized way to reach their destination. As we aware GPS is an outdoor application, GPS location is not accurate in indoor and small scale areas. This leads to an advanced research to improve the accuracy in GPS positing for the benefit of indoor applications. This research proposes a new iBeacons based Improved Indoor Positioning System for indoor positing application using Bluetooth low energy (BLE) beacons. This model helps the mobile application to find the exact location at micro-level scale. The objective of this research work is to design a potable indoor positing system (IPS) for indoor applications with at least 100m accuracy with in the inbuilt energy resource limitations. The proposed model has been built and verified in all the aspects. The location accuracy and energy efficiency of the proposed model is compared and found better than the existing models

Design of Continuous Indoor Navigation System Based on INS and Wifi

2013 ◽  
Vol 303-306 ◽  
pp. 2046-2049 ◽  
Author(s):  
Yi Hu ◽  
Lei Sheng ◽  
Shan Jun Zhang
Keyword(s):  
Navigation System ◽  
Smart Phone ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
High Price ◽  
Position Information ◽  
Positioning Method ◽  
Indoor Navigation System ◽  
Navigation Service

The application of navigation, such as guidance of pedestrians, requires a certain accuracy of continuous outdoor and indoor positioning. In outdoor environments GPS system has proved to be effective. However in indoor it is challenging to control the accuracy within 2 to 3 meters. At present several approaches have been developed for indoor positioning, such as RFID. But they are mainly been implemented in professional areas, for general user such as tourists and visual incapable users it is difficult to take advantage of these technologies because of the high price of terminal and the navigation service covered area is extremely limited. In this paper, a new approach of indoor navigation method is proposed to solve the problems of traditional methods. It is based on INS and wifi positioning technology. As hardware, wifi receiver, smart phone built-in accelerometer and digital compass are selected and investigated. User’s indoor position is first estimated by dead reckoning method with INS navigation system and then be recalibrated by wifi position information. Several experiments performed in the test verified the effectiveness of this indoor continuous positioning method described in this paper.

Fast visible light indoor positioning system based on smart phone

2017 ◽  
Vol 38 (3) ◽  
pp. 517-522
Author(s):  
Yang Zhen ◽  
Fang Junbin ◽  
Chen Zhe
Keyword(s):  
Visible Light ◽  
Smart Phone ◽  
Indoor Positioning ◽  
Positioning System ◽  
Indoor Positioning System

scholarly journals Error Analysis on Indoor Localization with Visible Light Communication

2019 ◽  
Vol 11 (4) ◽  
pp. 427
Author(s):  
Jun Yan ◽  
Bingcheng Zhu ◽  
Liang Chen ◽  
Jin Wang ◽  
Jingbin Liu
Keyword(s):  
Visible Light ◽  
Indoor Localization ◽  
Smart Phone ◽  
Visible Light Communication ◽  
Indoor Positioning ◽  
Light Signal ◽  
Indoor Navigation ◽  
Angle Of Arrival ◽  
Light Emitting ◽  
Indoor Scenarios

Affected by the complexity of the indoor environment, accurate indoor positioning is challenging in many localization based services (LBS). Recently, it has been recognized that, visible light communication (VLC) is promising for indoor navigation and positioning, due to the low implementation cost with marginal modification to the existing infrastructure and the possibility to achieve high accurate positioning results. Provided that the positions of the light emitting diodes (LEDs) are known to the receiver, the angle of arrival (AOA) of the light signal is able to be estimated by a camera embedded in a smart phone, and thus the position of the smart phone can be derived based on the triangulation. In this paper, the performance of the positioning accuracy is analyzed based on indoor positioning with VLC, and the analytical upper bound of location error is derived. Extensive simulation results have verified the theoretical analysis on the VLC-based localization approach in different indoor scenarios. In order to obtain better location performance, the principles of choosing reference LED and localization LED are also given.

scholarly journals Optimization-Based Wi-Fi Radio Map Construction for Indoor Positioning Using Only Smart Phones

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3095 ◽  
Author(s):  
Jian Tan ◽  
Xiangtao Fan ◽  
Shenghua Wang ◽  
Yingchao Ren
Keyword(s):  
Nearest Neighbor ◽  
Smart Phone ◽  
Dead Reckoning ◽  
Maximum Error ◽  
Optimization Method ◽  
Indoor Positioning ◽  
Factor Graph ◽  
K Nearest Neighbor ◽  
Site Survey ◽  
Radio Map

Fingerprinting-based Wi-Fi indoor positioning has great potential for positioning in GPS-denied areas. However, establishing a fingerprinting map (also called a radio map) prior to positioning (site survey) is normally a labor-intensive task. This paper proposes a method for easy site survey without need for any extra hardware. The user can conduct the site survey adopting only a smart phone. The collected inertial-based readings are processed using the pedestrian dead-reckoning algorithms to generate a raw trajectory. Then a factor graph optimization method is proposed to re-estimate the trajectory by adding constraints originated from collected Wi-Fi fingerprints and landmark positions. The proposed method is verified through an experiment in a mall. The mean positioning error is 1.10 m and the maximum error is 2.25 m. This level of positioning accuracy is considered sufficient for radio map generation purposes. A classical baseline algorithm, the k-Nearest Neighbor (kNN) algorithm, is adopted to test the positioning performance of the radio map (RM), which also validates the quality of the constructed RM from the proposed method.

Development of Indoor Positioning System using IMES for Smart Phone

2018 ◽  
Vol 138 (3) ◽  
pp. 193-203
Author(s):  
Takamasa Kawaguchi ◽  
Kenjiro Fujii ◽  
Makoto Tanikawara ◽  
Nobuaki Kubo
Keyword(s):  
Smart Phone ◽  
Indoor Positioning ◽  
Positioning System ◽  
Indoor Positioning System

scholarly journals Indore Navigation Mobile Application using Indore Positioning System (IPS)

2020 ◽  
Vol 2 (10) ◽  
pp. 5-7
Author(s):  
Anusha Sanampudi* ◽  
Keyword(s):  
Mobile Application ◽  
Smart Phone ◽  
Dead Reckoning ◽  
Steel Structures ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Smart Phones ◽  
Positioning System ◽  
Shopping Malls ◽  
Indoor Positioning System

Indoor Positioning system (IPS) is the technology that is used to locate smart phones, people or other objects inside a building where Global Positioning System (GPS) doesn’t work or lack precision such as airports, underground locations, parking, multi-storey buildings etc…There is no fixed standard for implementing IPS rather it could be customized according to the location chosen. IPS in turn uses a number of technologies such as Wi-Fi, Bluetooth, Beacons, magnetic positioning, dead reckoning etc…Among the various technologies available studies prove that Magnetic localization provides a most efficient solution for Indoor positioning. Our paper focuses on building an indoor navigation mobile application for a retail store that allows users to search for a product and navigate them to the particular aisle in which the product is located. There by enabling the application to be location sensitive and context aware. In order to collect magnetic fingerprints and convert the obtained data into latitude and longitude values we make use of an API called IndoorAtlas, which helps in locating smart phones inside a building using the accelerometer, gyroscope, magnetometer and Bluetooth in a mobile. Magnetic localization is the concept where deflections of magnetic field from the steel structures inside the building will be captured by the magnetometer and other sensors within a mobile and that will be used to locate a smart phone inside a building. The same application could be utilized for various use cases such as Supermarkets & Hypermarkets, museums & galleries, Libraries, Hospitals, Airports & stations, Shopping malls, Exhibition and Conferences.

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