Indoor Localization Techniques Based on Wireless Sensor Networks

Ahn, Hyo‐Sung; Yu, Wonpi

doi:10.5772/6998

Cited by 12 publications

(7 citation statements)

References 26 publications

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“…However, it has limitations in indoor environments due to the large attenuation caused by buildings' walls and ceilings [7]. To extend the capability of mobile localization applications in indoor environments, researchers worked on alternative solutions based on various types of signals like ultra wide band, WiFi, zigbee, bluetooth, etc [8], [9], [10]. One of the advantages of WiFi signals over the others is that one can rely only on the Access Points (APs) present inside the building, with no need to additional hardware.…”

Section: Introductionmentioning

confidence: 99%

Mobility-based Tracking Using WiFi RSS in Indoor Wireless Sensor Networks

Alshamaa

Mourad-Chehade

Honeiné

2018

2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)

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Tracking of mobile sensors is an important research issue in wireless sensor networks. This paper presents a zoningbased tracking technique that works efficiently in indoor environments. The targeted area is composed of several zones, the objective being to determine the zone of the mobile sensor in a real-time tracking process. The proposed method creates a belief functions framework that combines evidence using the sensors mobility and observations. To do this, a mobility model is proposed by using the previous state of the sensor and its assumed maximum speed. Also, an observation model is constructed based on fingerprints collected as WiFi signals strengths received from surrounding Access Points. Real experiments demonstrate the effectiveness of this approach and its competence compared to state-of-the-art methods.

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Section: Introductionmentioning

confidence: 99%

Mobility-based Tracking Using WiFi RSS in Indoor Wireless Sensor Networks

Alshamaa

Mourad-Chehade

Honeiné

2018

2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)

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“…However, it has limitations in indoor environments [4]. Alternative solutions consist of using other types of signals, that are available in closed environments, like ultra wide band, WiFi, zigbee, bluetooth,etc [5], [6], [7], [8]. One of the advantages of WiFi signals over the others is that one can rely only on the Access Points (APs) present inside the building, with no additional hardware.…”

Section: Introductionmentioning

confidence: 99%

Zoning-based localization in indoor sensor networks using belief functions theory

Alshamaa

Mourad-Chehade

Honeiné

2016

2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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Localization is an essential issue in wireless sensor networks to process the information retrieved by sensor nodes. This paper presents an indoor zoning-based localization technique that works efficiently in real environments. The targeted area is composed of several zones, the objective being to find the zone where the mobile node is instantly located. The proposed approach collects first strengths of received WiFi signals from neighboring access points and builds a fingerprints database. It then uses belief functions theory to combine all measured data and define an evidence framework, to be used afterwards for estimating the most probable node's zone. Real experiments demonstrate the effectiveness of this approach and its competence compared to state-of-the-art methods.

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“…In ubiquitous computing, locating user's mobile device is one of the key issues to enable transparent and immediate services to user. Several localization techniques have been proposed that are based on GPS [1], cellular [2][3][4] or Wi-Fi [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] technologies. Although GPS-based technology has been improved to get the accuracy of up to a few meters [1], it can only be applied for outdoor locations since GPS signals from the satellites can be blocked easily by buildings, trees and other obstacles.…”

Section: Introductionmentioning

confidence: 99%

“…Approaches using cellular technology [2][3][4] can work for both outdoor and indoor locations (covered by cell towers) but offers low accuracy (several hundred meters). Recently, many approaches using Wi-Fi (802.11) signals [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] have been proposed for indoor locations thanks to their high accuracy rate and the increasingly popularity of the 802.11 access points. According to [5,6], Wi-Fi based localization algorithms can be divided into four main categories: range-based, range-free (such as centroid [7,8]), scene matching (such as fingerprint [5,9]), aggregate and singular.…”

Section: Introductionmentioning

confidence: 99%

A Scalable Wi-Fi Based Localization Algorithm

Nguyen

2011

REV-JEC

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This paper proposes an applicable and scalable approach which allows deploying the fingerprint Wi-Fi localization algorithm for different mobile devices. The original fingerprint localization algorithm performs accurately when the mobile device used in the deployment phase is the same as the mobile device used in the training phase. However, when a different mobile device is used in the deployment phase, a time-consuming re-training step (in the order of hours or days) is required to achieve the equivalent degree of accuracy. Our proposed approach replaces this re-training step by a short period of calibration (in the order of a few minutes), which can be done transparently to the user. To validate our approach, we did an analysis on collected data from a large scale experiment (14 laptops and 2 smartphones with 224-hour of collected data) and evaluated the performance on the real devices.

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Indoor Localization Techniques Based on Wireless Sensor Networks

Cited by 12 publications

References 26 publications

Mobility-based Tracking Using WiFi RSS in Indoor Wireless Sensor Networks

Mobility-based Tracking Using WiFi RSS in Indoor Wireless Sensor Networks

Zoning-based localization in indoor sensor networks using belief functions theory

A Scalable Wi-Fi Based Localization Algorithm

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