Indoor Mobile Localization Based on Wi-Fi Fingerprint's Important Access Point

Pei, Jian; Zhang, Yunzhou; Fu, Wenyan; Liu, Huiyu; Su, Xiaolin

doi:10.1155/2015/429104

Cited by 83 publications

(47 citation statements)

References 18 publications

(23 reference statements)

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“…In a recent solution based on WAPs signal measurements has been proposed by [7]. In the solution, a modified fingerprinting algorithm has been implemented which selects the height/strong WAPs-RSS values in the vicinity, called important access points (IAP).…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Modified WiFi-RSS Fingerprint Technique to locate Indoors-Smartphones: FENG building at Koya University as a case study

Maghdid

Abdulrahman

Ahmed

et al. 2017

KJAR

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Positioning system used for different purposes and different services, many researches are going on to find a more accurate position with low error within high performance. There are many localization solutions with different architectures, configurations, accuracies and reliabilities for both outdoors and indoors. For example, Global Navigation Satellite System (GNSS) technology has been used for outdoors. Global Positioning System (GPS) is one of the most common outdoors tracking solutions in the world, for outdoors, however, when indoors; it could not be accurately tracked users by using a GPS system. This is because, when users enters into indoors the GPS signals will no longer available due to blocked by the roof of buildings and it is no longer considered as a viable option. WiFi Positioning System (WPS) can be used as an alternative solution to define users' position, especially when GPS signal is not available. Further, WPS is a low cost solution, because there is no need to deploying WiFi Access Points (WAPs) in the vicinity, as they are installed to access the Internet. In this paper, specifically, WiFi-RSS Fingerprinting technique is used to locate smartphones using WAPs signals with a modified calculation. The new modified calculation is to dynamic weighting of the WAPs RSS values based on the real-live indoors structure. The achieved positioning accuracy, based on several trial experiments, is up to 6 meters via the implemented algorithm in the MALTAB.

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Section: Related Workmentioning

confidence: 99%

“…Our proposed work is similar to [7], but it is different in a way of selecting the WAPs RSS values based on dynamic weighting of the fingerprints. That's mean, the dynamic weighting value will differs the WAPs signals in a real live measurements when the indoors structure will be changed.…”

Section: Related Workmentioning

confidence: 99%

Modified WiFi-RSS Fingerprint Technique to locate Indoors-Smartphones: FENG building at Koya University as a case study

Maghdid

Abdulrahman

Ahmed

et al. 2017

KJAR

View full text Add to dashboard Cite

show abstract

“…The second positioning approach is fingerprint-based positioning (Jiang et al 2015). In a general fingerprint localization methodology, the access point with the highest RSS value is denoted as the important access point (IAP).…”

Section: Fingerprint-based Positioningmentioning

confidence: 99%

Geofencing-Based Localization for 3d Data Acquisition Navigation

Nakagawa¹,

Kamio²,

Yasojima³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT: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.

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“…There are many ways to determine the position in indoor environment, by utilizing 802.11 b/g Wireless Local Area Network (WLAN) technology, Bluetooth, Radio Frequency Identification (RFID) and the others [8]. In many ways to determine position at indoor environment, the RSS fingerprint method is one of the most popular methods [9].…”

Section: Introductionmentioning

confidence: 99%

CAPTURE: A Mobile Based Indoor Positioning System using Wireless Indoor Positioning System

Dari

Suyoto

Pranowo

2018

Int. J. Interact. Mob. Technol.

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Abstract-The existence of mobile devices as a location pointing device using Global Positioning System (GPS) is a very common thing nowadays. The use of GPS as a tool to determine the location of course has a shortage when used indoors. Therefore, the used of indoor location-based services in a room that leverages the use of Access Point (AP) is very important. By using the information of the Received Signal Strength (RSS) obtained from AP, then the location of the device can be determined without the need to use GPS. This technique is called the location fingerprint technique using the characteristics of received RSS's fingerprint, then use it to determine the position. To get a more accurate position then authors used the K-Nearest Neighbor (KNN) method. KNN will use some of the data that obtained from some AP to assist in positioning the device. This solution of course would be able to determine the position of the devices in a storied building.

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Indoor Mobile Localization Based on Wi-Fi Fingerprint's Important Access Point

Cited by 83 publications

References 18 publications

Modified WiFi-RSS Fingerprint Technique to locate Indoors-Smartphones: FENG building at Koya University as a case study

Modified WiFi-RSS Fingerprint Technique to locate Indoors-Smartphones: FENG building at Koya University as a case study

Geofencing-Based Localization for 3d Data Acquisition Navigation

CAPTURE: A Mobile Based Indoor Positioning System using Wireless Indoor Positioning System

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