Context Sensitive Health Monitoring Using Fog Computing

Pinjari Hameed; Anand Paul

doi:10.1109/CSCI.2017.304

Context Sensitive Health Monitoring Using Fog Computing

Pinjari Hameed, Anand Paul

Kyungpook National University

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

Abstract

Health informatics has become one of the most researched area when it comes to application of Wireless Sensor Networks (WSNs). Wireless and wearable sensors have become prevalent devices to monitor patients at risk for chronic diseases. This helps ascertain that patients comply by the treatment plans and also safeguard them during sudden attacks. The amount of data that is gathered from various sensors are numerous. In this paper we propose to use fog computing to help monitor patients suffering from chronic diseases such that the data is collected and processed in an efficient manner. The main challenge would be to only sort out context sensitive data that is relevant to the health of the patient. Just having a simple sensor-to-cloud architecture is not viable and this is where having a fog computing layer makes a difference. This increases the efficiency of the entire system as it not only reduces the amount of data that is transported back and forth between the cloud and the sensors, but also eliminates the risk that a data center failure bears with it. We also analyse the security and deployment issues of this fog computing layer.

Original language	English
Title of host publication	Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
Editors	Fernando G. Tinetti, Quoc-Nam Tran, Leonidas Deligiannidis, Mary Qu Yang, Mary Qu Yang, Hamid R. Arabnia
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1747-1752
Number of pages	6
ISBN (Electronic)	9781538626528
DOIs	https://doi.org/10.1109/CSCI.2017.304
State	Published - 4 Dec 2018
Event	2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 - Las Vegas, United States Duration: 14 Dec 2017 → 16 Dec 2017

Publication series

Name	Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017

Conference

Conference	2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
Country/Territory	United States
City	Las Vegas
Period	14/12/17 → 16/12/17

Keywords

Cloud Computing
Fog Computing
Health Informatics
Wireless Sensor Networks

Access to Document

10.1109/CSCI.2017.304

Cite this

Hameed, P., & Paul, A. (2018). Context Sensitive Health Monitoring Using Fog Computing. In F. G. Tinetti, Q.-N. Tran, L. Deligiannidis, M. Q. Yang, M. Q. Yang, & H. R. Arabnia (Eds.), Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 (pp. 1747-1752). Article 8561069 (Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCI.2017.304

Hameed, Pinjari ; Paul, Anand. / Context Sensitive Health Monitoring Using Fog Computing. Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017. editor / Fernando G. Tinetti ; Quoc-Nam Tran ; Leonidas Deligiannidis ; Mary Qu Yang ; Mary Qu Yang ; Hamid R. Arabnia. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1747-1752 (Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017).

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title = "Context Sensitive Health Monitoring Using Fog Computing",

abstract = "Health informatics has become one of the most researched area when it comes to application of Wireless Sensor Networks (WSNs). Wireless and wearable sensors have become prevalent devices to monitor patients at risk for chronic diseases. This helps ascertain that patients comply by the treatment plans and also safeguard them during sudden attacks. The amount of data that is gathered from various sensors are numerous. In this paper we propose to use fog computing to help monitor patients suffering from chronic diseases such that the data is collected and processed in an efficient manner. The main challenge would be to only sort out context sensitive data that is relevant to the health of the patient. Just having a simple sensor-to-cloud architecture is not viable and this is where having a fog computing layer makes a difference. This increases the efficiency of the entire system as it not only reduces the amount of data that is transported back and forth between the cloud and the sensors, but also eliminates the risk that a data center failure bears with it. We also analyse the security and deployment issues of this fog computing layer.",

keywords = "Cloud Computing, Fog Computing, Health Informatics, Wireless Sensor Networks",

author = "Pinjari Hameed and Anand Paul",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 ; Conference date: 14-12-2017 Through 16-12-2017",

year = "2018",

month = dec,

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doi = "10.1109/CSCI.2017.304",

language = "English",

series = "Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017",

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Hameed, P & Paul, A 2018, Context Sensitive Health Monitoring Using Fog Computing. in FG Tinetti, Q-N Tran, L Deligiannidis, MQ Yang, MQ Yang & HR Arabnia (eds), Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017., 8561069, Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017, Institute of Electrical and Electronics Engineers Inc., pp. 1747-1752, 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017, Las Vegas, United States, 14/12/17. https://doi.org/10.1109/CSCI.2017.304

Context Sensitive Health Monitoring Using Fog Computing. / Hameed, Pinjari; Paul, Anand.
Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017. ed. / Fernando G. Tinetti; Quoc-Nam Tran; Leonidas Deligiannidis; Mary Qu Yang; Mary Qu Yang; Hamid R. Arabnia. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1747-1752 8561069 (Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017).

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

TY - GEN

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AU - Hameed, Pinjari

AU - Paul, Anand

PY - 2018/12/4

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N2 - Health informatics has become one of the most researched area when it comes to application of Wireless Sensor Networks (WSNs). Wireless and wearable sensors have become prevalent devices to monitor patients at risk for chronic diseases. This helps ascertain that patients comply by the treatment plans and also safeguard them during sudden attacks. The amount of data that is gathered from various sensors are numerous. In this paper we propose to use fog computing to help monitor patients suffering from chronic diseases such that the data is collected and processed in an efficient manner. The main challenge would be to only sort out context sensitive data that is relevant to the health of the patient. Just having a simple sensor-to-cloud architecture is not viable and this is where having a fog computing layer makes a difference. This increases the efficiency of the entire system as it not only reduces the amount of data that is transported back and forth between the cloud and the sensors, but also eliminates the risk that a data center failure bears with it. We also analyse the security and deployment issues of this fog computing layer.

AB - Health informatics has become one of the most researched area when it comes to application of Wireless Sensor Networks (WSNs). Wireless and wearable sensors have become prevalent devices to monitor patients at risk for chronic diseases. This helps ascertain that patients comply by the treatment plans and also safeguard them during sudden attacks. The amount of data that is gathered from various sensors are numerous. In this paper we propose to use fog computing to help monitor patients suffering from chronic diseases such that the data is collected and processed in an efficient manner. The main challenge would be to only sort out context sensitive data that is relevant to the health of the patient. Just having a simple sensor-to-cloud architecture is not viable and this is where having a fog computing layer makes a difference. This increases the efficiency of the entire system as it not only reduces the amount of data that is transported back and forth between the cloud and the sensors, but also eliminates the risk that a data center failure bears with it. We also analyse the security and deployment issues of this fog computing layer.

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A2 - Yang, Mary Qu

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017

Y2 - 14 December 2017 through 16 December 2017

ER -

Hameed P, Paul A. Context Sensitive Health Monitoring Using Fog Computing. In Tinetti FG, Tran QN, Deligiannidis L, Yang MQ, Yang MQ, Arabnia HR, editors, Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1747-1752. 8561069. (Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017). doi: 10.1109/CSCI.2017.304

Context Sensitive Health Monitoring Using Fog Computing

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