An efficient clustering with robust outlier mitigation for Wi-Fi fingerprint based indoor positioning

Sadhukhan, Pampa; Gain, Supriya; Dahal, Keshav; Chattopadhyay, Samiran; Garain, Nilkantha; Wang, Xinheng

doi:10.1016/j.asoc.2021.107549

Cited by 23 publications

(20 citation statements)

References 49 publications

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“…We plan to extend our method in the near future to detect the walking direction of the pedestrian along with step length estimation. We also aim to integrate our method with our previously proposed absolute position estimation technique presented in [42,43,44] to design a complete pedestrian navigation system.…”

Section: Conclusion and Future Research Scopementioning

confidence: 99%

Human Gait Modeling with Step Length Estimation based on Single Foot Mounted Inertial Sensors

Gayen

Sadhukhan

Chowdhury

et al. 2023

Preprint

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The rapid growth of mobile communication and pervasive computing technology has expanded the demand for location-based services in urban areas, which necessitate accurate localization and tracking of the user. Due to very poor performances of global positioning system (GPS) in indoor areas and urban canyons, various radio frequency (RF) technologies have been exploited by many researchers to design indoor positioning systems (IPSs) over the years. However, such RF based IPSs would work only in the presence of certain infrastructure. The emergence of low-cost inertial sensors like accelerometer, gyroscope etc., on the other hand, has motivated the researchers to design pedestrian dead reckoning (PDR) based IPSs as they do not depend on availability of any sort of infrastructure in the surrounding environment. Step length estimation (SLE) is an integral part of PDR based localization. We, thus, aim to design a SLE technique in this paper, by processing signal measurements collected from the inertial sensors attached to some body parts. Our proposed SLE method requires only a simple foot-mounted inertial sensor unit integrating three-axis accelerometer and gyroscope and it uses Butterworth low-pass filter to remove the noises from both acceleration and angular velocity signals. A normalized threshold and minimum time constraint-based peak-valley detection algorithm is also employed by our proposed method to calculate the swing phase duration. The proposed SLE technique uses only one user-specific parameter which is also calibrated for five different users in this paper. The performances of the proposed SLE technique are then evaluated and compared with some existing method in terms of accuracy to demonstrate the efficacy of the proposed method. Moreover, the relationships between the gait features and step length of the pedestrians as well as the same between their body mass index and the calibrated parameter are also examined in this paper.

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Section: Conclusion and Future Research Scopementioning

confidence: 99%

Human Gait Modeling with Step Length Estimation based on Single Foot Mounted Inertial Sensors

Gayen

Sadhukhan

Chowdhury

et al. 2023

Preprint

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“…At the same time, after completion of the design process, additional factors like power consumption, maintenance, and expanding the system to provide more services directly impact and increase the cost of the localization system. However, the cost of location-based systems has recently reduced as a result of the widespread use of smart terminal devices around the globe and the increment of the availability of wireless local area networks [74].…”

Section: Costmentioning

confidence: 99%

A Comprehensive Review of Indoor/Outdoor Localization Solutions in IoT era: Research Challenges and Future Perspectives

Asaad¹,

Maghdid²

2021

Preprint

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<p>The number of connected mobile devices and Internet of Things (IoT) is growing around us, rapidly. Since, most of the people daily activities are relying on these connected things or devices. Specifically, this past year (with COVID-19) changed daily life in abroad and this is increased the use of IoT enabled technologies in health sector, work, and play. Further, the most common service via using these technologies is the localization/positioning service for different applications including: geo-tagging, billing, contact tracing, health-care system, point-of-interest recommendations, social networking, security, and more. Despite the availability of a large number of localization solutions in the literature, the precision of localization cannot meet the needs of consumers. For that reason, this paper provides an in-depth investigation of the existing technologies and techniques in the localization field, within the IoT era. Furthermore, the benefits and drawbacks of each technique with enabled technologies are illustrated and a comparison between the utilized technologies in the localization is made. The paper as a guideline is also going through all of the metrics that may be used to assess the localization solutions. Finally, the state-of-the-art solutions are examined, with challenges and perspectives regarding indoors/outdoors environments are demonstrated.</p>

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“…We, thus, aim in this paper to lessen the positioning and storage overhead of the fingerprint positioning method as well as the negative impact of the time varying nature of RSS samples on the positioning accuracy. Our previously proposed efficient clustering strategy [8] employs average fusion policy to reduce the storage and positioning overhead of fingerprint positioning. However, such fusion policy fails to diminish the negative impact of RSS dataset's stochastic nature on the positioning accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the previously proposed clustering method selects only the RP obtaining maximum RSS from the AP associated with its cluster as the initial point of data fusion within that cluster. So, the effect of considering some other RP as the initial point of data fusion on the performances of the proposed positioning system has not been well investigated in our prior work [8]. We, therefore, propose in this paper a novel weighted fusion based efficient clustering strategy that considers both RPs obtaining either maximum or minimum RSS from the corresponding AP as the potential initiator of data fusion within a cluster to improve the positioning performances of fingerprint method.…”

Section: Introductionmentioning

confidence: 99%

A Novel Weighted Fusion Based Efficient Clustering for Improved Wi-Fi Fingerprint Indoor Positioning

Sadhukhan

Dahal

Das

2023

IEEE Trans. Wireless Commun.

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An efficient clustering with robust outlier mitigation for Wi-Fi fingerprint based indoor positioning

Cited by 23 publications

References 49 publications

Human Gait Modeling with Step Length Estimation based on Single Foot Mounted Inertial Sensors

Human Gait Modeling with Step Length Estimation based on Single Foot Mounted Inertial Sensors

A Comprehensive Review of Indoor/Outdoor Localization Solutions in IoT era: Research Challenges and Future Perspectives

A Novel Weighted Fusion Based Efficient Clustering for Improved Wi-Fi Fingerprint Indoor Positioning

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