Adaptive energy optimization algorithm for internet of medical things

Sandeep Pirbhulal, Wanqing Wu, Subhas Chandra Mukhopadhyay, Guanglin Li

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Abstract

Emerging trends in smart healthcare have revolutionized the medical market from child care to elderly patients. Internet of medical things (IoMT) in association with other state-of-the-art technologies playing the significant role in every field, but due to its autonomous and self-adaptive nature there is a great attention of everyone from each field particularly healthcare domain. For the disabled patients, it is very vital that a system must be self-driven and adaptive for facilitating them at every walk of their lives. In this regard, adaptive strategies with intelligent systems are the optimal solution for the medical applications. One of the critical challenges for the all miniaturized sensor devices is their resource-constrained nature while coping-up with the several issues during information exchanging and sharing knowledge with each other and intended device. Thus by keeping this dire need in mind, it is important to focus the adaptive transmission power control (TPC) based mechanism to fairly allocate the resources and facilitate the disabled patients. This paper proposes the novel adaptive energy optimization algorithm (AEOA) by adjusting the characteristics of the healthcare platform. Experimental results reveal that proposed AEOA outperforms the conventional methods by saving energy in the IoMT.

LanguageEnglish
Title of host publication2018 12th International Conference on Sensing Technology (ICST)
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages269-272
Number of pages4
ISBN (Electronic)9781538651476, 9781538651469
ISBN (Print)9781538651483
DOIs
Publication statusPublished - 2018
Event12th International Conference on Sensing Technology, ICST 2018 - Limerick, Ireland
Duration: 4 Dec 20186 Dec 2018

Publication series

Name
ISSN (Print)2156-8065
ISSN (Electronic)2156-8073

Conference

Conference12th International Conference on Sensing Technology, ICST 2018
CountryIreland
CityLimerick
Period4/12/186/12/18

Fingerprint

Internet
Medical applications
Intelligent systems
Power control
Energy conservation
Sensors

Keywords

  • IoMT
  • Adaptive Healthcare
  • Energy Efficiency

Cite this

Pirbhulal, S., Wu, W., Mukhopadhyay, S. C., & Li, G. (2018). Adaptive energy optimization algorithm for internet of medical things. In 2018 12th International Conference on Sensing Technology (ICST) (pp. 269-272). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICSensT.2018.8603601
Pirbhulal, Sandeep ; Wu, Wanqing ; Mukhopadhyay, Subhas Chandra ; Li, Guanglin. / Adaptive energy optimization algorithm for internet of medical things. 2018 12th International Conference on Sensing Technology (ICST). Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2018. pp. 269-272
@inproceedings{4a5797ad87114c788650b307ebdeff1a,
title = "Adaptive energy optimization algorithm for internet of medical things",
abstract = "Emerging trends in smart healthcare have revolutionized the medical market from child care to elderly patients. Internet of medical things (IoMT) in association with other state-of-the-art technologies playing the significant role in every field, but due to its autonomous and self-adaptive nature there is a great attention of everyone from each field particularly healthcare domain. For the disabled patients, it is very vital that a system must be self-driven and adaptive for facilitating them at every walk of their lives. In this regard, adaptive strategies with intelligent systems are the optimal solution for the medical applications. One of the critical challenges for the all miniaturized sensor devices is their resource-constrained nature while coping-up with the several issues during information exchanging and sharing knowledge with each other and intended device. Thus by keeping this dire need in mind, it is important to focus the adaptive transmission power control (TPC) based mechanism to fairly allocate the resources and facilitate the disabled patients. This paper proposes the novel adaptive energy optimization algorithm (AEOA) by adjusting the characteristics of the healthcare platform. Experimental results reveal that proposed AEOA outperforms the conventional methods by saving energy in the IoMT.",
keywords = "IoMT, Adaptive Healthcare, Energy Efficiency",
author = "Sandeep Pirbhulal and Wanqing Wu and Mukhopadhyay, {Subhas Chandra} and Guanglin Li",
year = "2018",
doi = "10.1109/ICSensT.2018.8603601",
language = "English",
isbn = "9781538651483",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "269--272",
booktitle = "2018 12th International Conference on Sensing Technology (ICST)",
address = "United States",

}

Pirbhulal, S, Wu, W, Mukhopadhyay, SC & Li, G 2018, Adaptive energy optimization algorithm for internet of medical things. in 2018 12th International Conference on Sensing Technology (ICST). Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 269-272, 12th International Conference on Sensing Technology, ICST 2018, Limerick, Ireland, 4/12/18. https://doi.org/10.1109/ICSensT.2018.8603601

Adaptive energy optimization algorithm for internet of medical things. / Pirbhulal, Sandeep; Wu, Wanqing; Mukhopadhyay, Subhas Chandra; Li, Guanglin.

2018 12th International Conference on Sensing Technology (ICST). Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 269-272.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

TY - GEN

T1 - Adaptive energy optimization algorithm for internet of medical things

AU - Pirbhulal, Sandeep

AU - Wu, Wanqing

AU - Mukhopadhyay, Subhas Chandra

AU - Li, Guanglin

PY - 2018

Y1 - 2018

N2 - Emerging trends in smart healthcare have revolutionized the medical market from child care to elderly patients. Internet of medical things (IoMT) in association with other state-of-the-art technologies playing the significant role in every field, but due to its autonomous and self-adaptive nature there is a great attention of everyone from each field particularly healthcare domain. For the disabled patients, it is very vital that a system must be self-driven and adaptive for facilitating them at every walk of their lives. In this regard, adaptive strategies with intelligent systems are the optimal solution for the medical applications. One of the critical challenges for the all miniaturized sensor devices is their resource-constrained nature while coping-up with the several issues during information exchanging and sharing knowledge with each other and intended device. Thus by keeping this dire need in mind, it is important to focus the adaptive transmission power control (TPC) based mechanism to fairly allocate the resources and facilitate the disabled patients. This paper proposes the novel adaptive energy optimization algorithm (AEOA) by adjusting the characteristics of the healthcare platform. Experimental results reveal that proposed AEOA outperforms the conventional methods by saving energy in the IoMT.

AB - Emerging trends in smart healthcare have revolutionized the medical market from child care to elderly patients. Internet of medical things (IoMT) in association with other state-of-the-art technologies playing the significant role in every field, but due to its autonomous and self-adaptive nature there is a great attention of everyone from each field particularly healthcare domain. For the disabled patients, it is very vital that a system must be self-driven and adaptive for facilitating them at every walk of their lives. In this regard, adaptive strategies with intelligent systems are the optimal solution for the medical applications. One of the critical challenges for the all miniaturized sensor devices is their resource-constrained nature while coping-up with the several issues during information exchanging and sharing knowledge with each other and intended device. Thus by keeping this dire need in mind, it is important to focus the adaptive transmission power control (TPC) based mechanism to fairly allocate the resources and facilitate the disabled patients. This paper proposes the novel adaptive energy optimization algorithm (AEOA) by adjusting the characteristics of the healthcare platform. Experimental results reveal that proposed AEOA outperforms the conventional methods by saving energy in the IoMT.

KW - IoMT

KW - Adaptive Healthcare

KW - Energy Efficiency

UR - http://www.scopus.com/inward/record.url?scp=85061494681&partnerID=8YFLogxK

U2 - 10.1109/ICSensT.2018.8603601

DO - 10.1109/ICSensT.2018.8603601

M3 - Conference proceeding contribution

SN - 9781538651483

SP - 269

EP - 272

BT - 2018 12th International Conference on Sensing Technology (ICST)

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

ER -

Pirbhulal S, Wu W, Mukhopadhyay SC, Li G. Adaptive energy optimization algorithm for internet of medical things. In 2018 12th International Conference on Sensing Technology (ICST). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2018. p. 269-272 https://doi.org/10.1109/ICSensT.2018.8603601