A fog computing approach for localization in WSN

Kriti Bhargava; Stepan Ivanov

doi:10.1109/PIMRC.2017.8292245

A fog computing approach for localization in WSN

Kriti Bhargava, Stepan Ivanov

Waterford Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

13 Citations (Scopus)

Abstract

The Fog Computing paradigm proposes an extension of the cloud-based computing to the network edges in the Internet of Things. It facilitates localized analysis closer to the data sources for improved responsiveness of the system as well as cloud-based learning for historical analysis. In this paper, we present our fog-enabled Wireless Sensor Network (WSN) system for activity monitoring and localization in the context of Ambient Assisted Living. Our WSN architecture consists of two types of devices - a wearable sensor device and a cloud gateway node. We discuss our Edge Mining approach for real-time activity classification on the sensor device as well as the Genetic Algorithm used for cloud-based analysis. The design of our analytical framework together with the communication model addresses the challenge of sensor-cloud integration. We evaluate the performance of our system for outdoor localization of the elderly. The analysis is based on acceleration data collected using our wearable device across different activity sequences obtained from the Kasteren dataset. © 2017 IEEE.

Original language	English
Title of host publication	IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-7
Number of pages	7
ISBN (Print)	9781538635315
DOIs	https://doi.org/10.1109/PIMRC.2017.8292245
Publication status	Published - 14 Feb 2018
Event	28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications - Montreal, Canada Duration: 8 Oct 2017 → 13 Oct 2017 http://pimrc2017.ieee-pimrc.org/

Publication series

Name	IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Volume	2017-October

Conference

Conference	28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications
Abbreviated title	PIMRC
Country/Territory	Canada
City	Montreal
Period	8/10/17 → 13/10/17
Internet address	http://pimrc2017.ieee-pimrc.org/

Access to Document

10.1109/PIMRC.2017.8292245

http://www.mendeley.com/research/fog-computing-approach-localization-wsn

Cite this

Bhargava, K., & Ivanov, S. (2018). A fog computing approach for localization in WSN. In IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC (pp. 1-7). (IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC; Vol. 2017-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PIMRC.2017.8292245

A fog computing approach for localization in WSN. / Bhargava, Kriti; Ivanov, Stepan.
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-7 (IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC; Vol. 2017-October).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Bhargava, K & Ivanov, S 2018, A fog computing approach for localization in WSN. in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, vol. 2017-October, Institute of Electrical and Electronics Engineers Inc., pp. 1-7, 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications , Montreal, Quebec, Canada, 8/10/17. https://doi.org/10.1109/PIMRC.2017.8292245

@inbook{0f324a094edf4ed9ab27ae1cbed6afcc,

title = "A fog computing approach for localization in WSN",

abstract = "The Fog Computing paradigm proposes an extension of the cloud-based computing to the network edges in the Internet of Things. It facilitates localized analysis closer to the data sources for improved responsiveness of the system as well as cloud-based learning for historical analysis. In this paper, we present our fog-enabled Wireless Sensor Network (WSN) system for activity monitoring and localization in the context of Ambient Assisted Living. Our WSN architecture consists of two types of devices - a wearable sensor device and a cloud gateway node. We discuss our Edge Mining approach for real-time activity classification on the sensor device as well as the Genetic Algorithm used for cloud-based analysis. The design of our analytical framework together with the communication model addresses the challenge of sensor-cloud integration. We evaluate the performance of our system for outdoor localization of the elderly. The analysis is based on acceleration data collected using our wearable device across different activity sequences obtained from the Kasteren dataset. {\textcopyright} 2017 IEEE.",

author = "Kriti Bhargava and Stepan Ivanov",

year = "2018",

month = feb,

day = "14",

doi = "10.1109/PIMRC.2017.8292245",

language = "English",

isbn = "9781538635315",

series = "IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--7",

booktitle = "IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC",

address = "United States",

note = "28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications , PIMRC ; Conference date: 08-10-2017 Through 13-10-2017",

url = "http://pimrc2017.ieee-pimrc.org/",

}

TY - CHAP

T1 - A fog computing approach for localization in WSN

AU - Bhargava, Kriti

AU - Ivanov, Stepan

PY - 2018/2/14

Y1 - 2018/2/14

N2 - The Fog Computing paradigm proposes an extension of the cloud-based computing to the network edges in the Internet of Things. It facilitates localized analysis closer to the data sources for improved responsiveness of the system as well as cloud-based learning for historical analysis. In this paper, we present our fog-enabled Wireless Sensor Network (WSN) system for activity monitoring and localization in the context of Ambient Assisted Living. Our WSN architecture consists of two types of devices - a wearable sensor device and a cloud gateway node. We discuss our Edge Mining approach for real-time activity classification on the sensor device as well as the Genetic Algorithm used for cloud-based analysis. The design of our analytical framework together with the communication model addresses the challenge of sensor-cloud integration. We evaluate the performance of our system for outdoor localization of the elderly. The analysis is based on acceleration data collected using our wearable device across different activity sequences obtained from the Kasteren dataset. © 2017 IEEE.

AB - The Fog Computing paradigm proposes an extension of the cloud-based computing to the network edges in the Internet of Things. It facilitates localized analysis closer to the data sources for improved responsiveness of the system as well as cloud-based learning for historical analysis. In this paper, we present our fog-enabled Wireless Sensor Network (WSN) system for activity monitoring and localization in the context of Ambient Assisted Living. Our WSN architecture consists of two types of devices - a wearable sensor device and a cloud gateway node. We discuss our Edge Mining approach for real-time activity classification on the sensor device as well as the Genetic Algorithm used for cloud-based analysis. The design of our analytical framework together with the communication model addresses the challenge of sensor-cloud integration. We evaluate the performance of our system for outdoor localization of the elderly. The analysis is based on acceleration data collected using our wearable device across different activity sequences obtained from the Kasteren dataset. © 2017 IEEE.

U2 - 10.1109/PIMRC.2017.8292245

DO - 10.1109/PIMRC.2017.8292245

M3 - Chapter

SN - 9781538635315

T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC

SP - 1

EP - 7

BT - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications

Y2 - 8 October 2017 through 13 October 2017

ER -

A fog computing approach for localization in WSN

Abstract

Publication series

Conference

Access to Document

Fingerprint

Cite this