research-article

An Energy-efficient and Lightweight Indoor Localization System for Internet-of-Things (IoT) Environments

Authors:

Myeongcheol Kwak,

Youngmong Park,

Taekyoung KwonAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 2, Issue 1

Article No.: 17, Pages 1 - 28

https://doi.org/10.1145/3191749

Published: 26 March 2018 Publication History

Abstract

Each and every spatial point in an indoor space has its own distinct and stable fingerprint, which arises owing to the distortion of the magnetic field induced by the surrounding steel and iron structures. This phenomenon makes many indoor positioning techniques rely on the magnetic field as an important source of localization. Most of the existing studies, however, have leveraged smartphones that have a relatively high computational power and many sensors. Thus, their algorithmic complexity is usually high, especially for commercial location-based services. In this paper, we present an energy-efficient and lightweight system that utilizes the magnetic field for indoor positioning in Internet of Things (IoT) environments. We propose a new hardware design of an IoT device that has a BLE interface and two sensors (magnetometer and accelerometer), with the lifetime of one year when using a coin-size battery. We further propose an augmented particle filter framework that features a robust motion model and a localization heuristic with small sensory data. The prototype-based evaluation shows that the proposed system achieves a median accuracy of 1.62 m for an office building, while exhibiting low computational complexity and high energy efficiency.

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Cited By

Khodamoradi FRezazadeh JAyoade J(2024)Accurate Indoor Localization with IoT Devices and Advanced Fingerprinting MethodsAlgorithms10.3390/a1712054417:12(544)Online publication date: 2-Dec-2024
https://doi.org/10.3390/a17120544
Zhou HMaekawa T(2024)Predicting Signal Reception Information from GNSS Satellites in Indoor Environments without Site Survey: Towards Opportunistic Indoor Positioning Based on GNSS FingerprintingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785548:3(1-30)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678554
Shabaz MSoni M(2024)Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagneticMeasurement: Sensors10.1016/j.measen.2024.10110733(101107)Online publication date: Jun-2024
https://doi.org/10.1016/j.measen.2024.101107
Show More Cited By

Index Terms

An Energy-efficient and Lightweight Indoor Localization System for Internet-of-Things (IoT) Environments
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Sensor devices and platforms
2. Human-centered computing
  1. Ubiquitous and mobile computing

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 2, Issue 1

March 2018

1370 pages

EISSN:2474-9567

DOI:10.1145/3200905

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Copyright © 2018 ACM.

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Publication History

Published: 26 March 2018

Accepted: 01 January 2018

Revised: 01 November 2017

Received: 01 August 2017

Published in IMWUT Volume 2, Issue 1

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Ministry of Education of the Republic of Korea and the National Research Foundation of Korea

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Cited By

Khodamoradi FRezazadeh JAyoade J(2024)Accurate Indoor Localization with IoT Devices and Advanced Fingerprinting MethodsAlgorithms10.3390/a1712054417:12(544)Online publication date: 2-Dec-2024
https://doi.org/10.3390/a17120544
Zhou HMaekawa T(2024)Predicting Signal Reception Information from GNSS Satellites in Indoor Environments without Site Survey: Towards Opportunistic Indoor Positioning Based on GNSS FingerprintingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785548:3(1-30)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678554
Shabaz MSoni M(2024)Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagneticMeasurement: Sensors10.1016/j.measen.2024.10110733(101107)Online publication date: Jun-2024
https://doi.org/10.1016/j.measen.2024.101107
Namee KSrikamta NKaewkajone TThierchot TPolpinij JKaewsaeng-On R(2023)Enhancing Indoor Positioning Accuracy: A Comprehensive Study on Euclidean Distance, Trilateration, Wi-Fi RTT and FTM Protocol IntegrationProceedings of the 2023 6th International Conference on Computational Intelligence and Intelligent Systems10.1145/3638209.3638235(173-180)Online publication date: 25-Nov-2023
https://dl.acm.org/doi/10.1145/3638209.3638235
Zhang JDai RRjob AWang RHamauon RCandell JBailey TFraser VGuillamet MLu C(2023)Contact Tracing for Healthcare Workers in an Intensive Care UnitProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36109247:3(1-23)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610924
He TNiu QLiu N(2023)GC-LocProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35694956:4(1-27)Online publication date: 11-Jan-2023
https://dl.acm.org/doi/10.1145/3569495
Zhou HMaekawa T(2023)GPS-assisted Indoor Pedestrian Dead ReckoningProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35694676:4(1-36)Online publication date: 11-Jan-2023
https://dl.acm.org/doi/10.1145/3569467
Saylam AGüzeliş CRodoplu V(2023)Machine Learning Enabled Sleep Time Estimation (MLE-STE) Architecture for Indoor Positioning in Energy-Efficient Mobile Internet of Things2023 IEEE 9th World Forum on Internet of Things (WF-IoT)10.1109/WF-IoT58464.2023.10539448(01-06)Online publication date: 12-Oct-2023
https://doi.org/10.1109/WF-IoT58464.2023.10539448
Shu MChen GZhang ZXu L(2023)Indoor Geomagnetic Positioning Using Direction-Aware Multiscale Recurrent Neural NetworksIEEE Sensors Journal10.1109/JSEN.2022.322795223:3(3321-3333)Online publication date: 1-Feb-2023
https://doi.org/10.1109/JSEN.2022.3227952
Guo DGu CJiang LLuo WTan R(2022)ILLOCProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35172456:1(1-26)Online publication date: 29-Mar-2022
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