EconPapers    
Economics at your fingertips  
 

Knowledge-based health service considering user convenience using hybrid Wi-Fi P2P

Kyungyong Chung (), Joo-Chang Kim () and Roy C. Park ()
Additional contact information
Kyungyong Chung: Sangji University
Joo-Chang Kim: Sangji University
Roy C. Park: Dongseo University

Information Technology and Management, 2016, vol. 17, issue 1, No 7, 67-80

Abstract: Abstract Recently, with changing paradigms in health, the focus of healthcare is shifting from treatment after contracting disease to prevention and early diagnosis of disease. Accordingly, the healthcare paradigm is changing from diagnosis and treatment to preventive management, emphasizing prevention of chronic diseases, such as obesity. In particular, obesity in children and adolescents has become a global issue. Lifestyle and health management using BT–IT convergence is needed to improve and manage the health of children and adolescents, and convenience and accessibility must be improved. For that, use of a machine-to-machine (M2M) u-health cluster that allows wireless network connection is increasing, along with wireless networks for measuring biometrics. Expanded to communications between people and objects as well as between objects, M2M refers to the next-generation convergence infra-architecture that offers intelligent services through various media. Because various wireless devices form a cluster when building a service platform using M2M, when the number of users with various M2M devices increases, data traffic increases and causes network overload, deteriorating system performance. To solve this problem, services are increasingly being built by combining a conventional network and Wi-Fi technology. However, in an M2M network, there is a limitation due to low transfer speed, because the network processes biometrics and data through different sensor nodes, and wireless communications based on the system is composed of different wireless sensor nodes. Thus, in this paper, we proposed a knowledge-based health service considering user convenience using a hybrid wireless fidelity (Wi-Fi) peer-to-peer (P2P) architecture. For knowledge-based health services in conventional M2M-based smart health services, hybrid Wi-Fi P2P and wireless devices must be linked. Because there are different ways to link hybrid Wi-Fi P2P devices, depending on the network environment, in this study, a dynamic configuration mechanism is applied to Wi-Fi P2P linkage of wireless devices in an M2M environment. The proposed service provides a high-quality health service (whenever patients use the knowledge-based health service) by building a network using a dispersed cross-layer optimization algorithm that optimizes variables of the transmission control protocol/internet protocol stack in order to improve the energy efficiency of the u-health sensor network and system reliability.

Keywords: u-Healthcare; Knowledge-based health; M2M; Hybrid Wi-Fi; P2P; Human UX/UI; Healthcare; Chronic disease (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s10799-015-0241-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infotm:v:17:y:2016:i:1:d:10.1007_s10799-015-0241-5

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10799

DOI: 10.1007/s10799-015-0241-5

Access Statistics for this article

Information Technology and Management is currently edited by Raymond Patterson and Erik Rolland

More articles in Information Technology and Management from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:infotm:v:17:y:2016:i:1:d:10.1007_s10799-015-0241-5