A RSSI-Based Location System in Coal Mine

Tian, Junfang; Hui-chang, Shi; Wenliang, Guo; Zhou, Ya

doi:10.1109/cjmw.2008.4772399

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…The location-sensing methods for RFID localization system include TOA(Time of Arrival) [9], TDOA(Time Difference of Arrival) [10], RSSI(Received Signal Strength Indication) [11][12][13], AOA(Angle Of Arrival) [14], and PDoA(Phase Difference of Arrival) [15], etc. Most of these methods suffer from high cost or the localization error problem which is caused by multi-path effect [16].…”

Section: Introductionmentioning

confidence: 99%

An Advanced RFID Localization Algorithm Based on Region Division and Error Compensation

2013

KSII TIIS

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In RSSI-based RFID(Radio Frequency IDentification) indoor localization system, the signal path loss model of each sub-region is different from others in the whole localization area due to the influence of the multi-path phenomenon and other environmental factors. Therefore, this paper divides the localization area into many sub-regions and constructs separately the signal path loss model of each sub-region. Then an improved LANDMARC method is proposed. Firstly, the deployment principle of RFID readers and tags is presented for constructing localization sub-region. Secondly, the virtual reference tags are introduced to create a virtual signal strength space with RFID readers and real reference tags in every sub-region. Lastly, k nearest neighbor (KNN) algorithm is used to locate the target object and an error compensating algorithm is proposed for correcting localization result. The results in real application show that the new method enhances the positioning accuracy to 18.2% and reduces the time cost to 30% of the original LANDMARC method without additional tags and readers.

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Section: Introductionmentioning

confidence: 99%

An Advanced RFID Localization Algorithm Based on Region Division and Error Compensation

2013

KSII TIIS

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RSSI Based Indoor Localization for Smartphone Using Fixed and Mobile Wireless Node

O’Brien

Ahamed

Smith

2013

2013 IEEE 37th Annual Computer Software and Applications Conference

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Nowadays with the dispersion of wireless networks, smartphones and diverse related services, different localization techniques have been developed. Global Positioning System (GPS) has a high rate of accuracy for outdoor localization but the signal is not available inside of buildings. Also other existing methods for indoor localization have low accuracy. In addition, they use fixed infrastructure support. In this paper, we present a novel system for indoor localization, which also works well outside. We have developed a mathematical model for estimating location (distance and direction) of a mobile device using wireless technology. Our experimental results on Smartphones (Android and iOS) show good accuracy (an error less than 2.5 meters). We have also used our developed system in asset tracking and complex activity recognition.

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An approach to localization in crowded area

Ahsan

Drew

et al. 2016

2016 IEEE 18th International Conference on E-Health Networking, Applications and Services (Healthcom)

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A RSSI-Based Location System in Coal Mine

Cited by 4 publications

References 7 publications

An Advanced RFID Localization Algorithm Based on Region Division and Error Compensation

An Advanced RFID Localization Algorithm Based on Region Division and Error Compensation

RSSI Based Indoor Localization for Smartphone Using Fixed and Mobile Wireless Node

An approach to localization in crowded area

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