Robust IoT-based nursing-care support system with smart bio-objects View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-11

AUTHORS

Cheng-Fa Chiang, Fang-Ming Hsu, Kuo-Hui Yeh

ABSTRACT

BACKGROUND: The significant advancement in the mobile sensing technologies has brought great interests on application development for the Internet-of-Things (IoT). With the advantages of contactlessness data retrieval and efficient data processing of intelligent IoT-based objects, versatile innovative types of on-demand medical relevant services have promptly been developed and deployed. Critical characteristics involved within the data processing and operation must thoroughly be considered. To achieve the efficiency of data retrieval and the robustness of communications among IoT-based objects, sturdy security primitives are required to preserve data confidentiality and entity authentication. METHODS: A robust nursing-care support system is developed for efficient and secure communication among mobile bio-sensors, active intelligent objects, the IoT gateway and the backend nursing-care server in which further data analysis can be performed to provide high-quality and on-demand nursing-care service. RESULTS: We realize the system implementation with an IoT-based testbed, i.e. the Raspberry PI II platform, to present the practicability of the proposed IoT-oriented nursing-care support system in which a user-friendly computation cost, i.e. 6.33 ms, is required for a normal session of our proposed system. Based on the protocol analysis we conducted, the security robustness of the proposed nursing-care support system is guaranteed. CONCLUSIONS: According to the protocol analysis and performance evaluation, the practicability of the proposed method is demonstrated. In brief, we can claim that our proposed system is very suitable for IoT-based environments and will be a highly competitive candidate for the next generation of nursing-care service systems. More... »

PAGES

154

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12938-018-0582-5

DOI

http://dx.doi.org/10.1186/s12938-018-0582-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107916735

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30396339


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