Time to forge ahead: The Internet of Things for healthcare

被引:12
作者
Furtado, Denzil [1 ,2 ]
Gygax, Andre F. [3 ]
Chan, Chien Aun [4 ]
Bush, Ashley I. [5 ]
机构
[1] Univ Melbourne, Melbourne Dementia Res Ctr, Melbourne, Vic 3010, Australia
[2] Univ Melbourne, Dept Chem Engn, Melbourne, Vic 3010, Australia
[3] Univ Melbourne, Fac Business & Econ, Melbourne, Vic 3010, Australia
[4] Univ Melbourne, Dept Elect & Elect Engn, Melbourne, Vic 3010, Australia
[5] Univ Melbourne, Florey Inst Neurosci & Mental Hlth, Melbourne, Vic 3010, Australia
关键词
Internet of Things; Healthcare; Information; Fog computing; Arti ficial intelligence; Machine learning; Big data; COVID-19; pandemic; BIG-DATA; DRUG SHORTAGES; AGGREGATION SCHEME; FOG; PRIVACY; SECURITY; SMART; ARCHITECTURE; CHALLENGES; FUTURE;
D O I
10.1016/j.dcan.2022.06.007
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Situated at the intersection of technology and medicine, the Internet of Things (IoT) holds the promise of addressing some of healthcare's most pressing challenges, from medical error, to chronic drug shortages, to overburdened hospital systems, to dealing with the COVID-19 pandemic. However, despite considerable recent technological advances, the pace of successful implementation of promising IoT healthcare initiatives has been slow. To inspire more productive collaboration, we present here a simple-but surprisingly underrated-problem-oriented approach to developing healthcare technologies. To further assist in this effort, we reviewed the various commercial, regulatory, social/cultural, and technological factors in the development of the IoT. We propose that fog computing-a technological paradigm wherein the burden of computing is shifted from a centralized cloud server closer to the data source-offers the greatest promise for building a robust and scalable healthcare IoT ecosystem. To this end, we explore the key enabling technologies that underpin the fog architecture, from the sensing layer all the way up to the cloud. It is our hope that ongoing advances in sensing, communications, cryptography, storage, machine learning, and artificial intelligence will be leveraged in meaningful ways to generate unprecedented medical intelligence and thus drive improvements in the health of many people.
引用
收藏
页码:223 / 235
页数:13
相关论文
共 130 条
[61]   The Internet of Things for Health Care: A Comprehensive Survey [J].
Islam, S. M. Riazul ;
Kwak, Daehan ;
Kabir, Md. Humaun ;
Hossain, Mahmud ;
Kwak, Kyung-Sup .
IEEE ACCESS, 2015, 3 :678-708
[62]   An IoT-Oriented Data Storage Framework in Cloud Computing Platform [J].
Jiang, Lihong ;
Xu, Li Da ;
Cai, Hongming ;
Jiang, Zuhai ;
Bu, Fenglin ;
Xu, Boyi .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2014, 10 (02) :1443-1451
[63]   Impact of drug shortages on U.S. health systems [J].
Kaakeh, Rola ;
Sweet, Burgunda V. ;
Reilly, Cynthia ;
Bush, Colleen ;
DeLoach, Sherry ;
Higgins, Barb ;
Clark, Angela M. ;
Stevenson, James .
AMERICAN JOURNAL OF HEALTH-SYSTEM PHARMACY, 2011, 68 (19) :1811-1819
[64]   Considering complexity in healthcare systems [J].
Kannampallil, Thomas G. ;
Schauer, Guido F. ;
Cohen, Trevor ;
Patel, Vimla L. .
JOURNAL OF BIOMEDICAL INFORMATICS, 2011, 44 (06) :943-947
[65]  
Katsuyama J., 2018, KTVU FOX NEWS
[66]   Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System [J].
Kiral-Kornek, Isabell ;
Roy, Subhrajit ;
Nurse, Ewan ;
Mashford, Benjamin ;
Karoly, Philippa ;
Carroll, Thomas ;
Payne, Daniel ;
Saha, Susmita ;
Baldassano, Steven ;
O'Brien, Terence ;
Grayden, David ;
Cook, Mark ;
Freestone, Dean ;
Harrer, Stefan .
EBIOMEDICINE, 2018, 27 :103-111
[67]  
Koh Hian Chye, 2005, J Healthc Inf Manag, V19, P64
[68]   Fog Computing in Healthcare-A Review and Discussion [J].
Kraemer, Frank Alexander ;
Braten, Anders Eivind ;
Tamkittikhun, Nattachart ;
Palma, David .
IEEE ACCESS, 2017, 5 :9206-9222
[69]   Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019 [J].
Lai, Jianbo ;
Ma, Simeng ;
Wang, Ying ;
Cai, Zhongxiang ;
Hu, Jianbo ;
Wei, Ning ;
Wu, Jiang ;
Du, Hui ;
Chen, Tingting ;
Li, Ruiting ;
Tan, Huawei ;
Kang, Lijun ;
Yao, Lihua ;
Huang, Manli ;
Wang, Huafen ;
Wang, Gaohua ;
Liu, Zhongchun ;
Hu, Shaohua .
JAMA NETWORK OPEN, 2020, 3 (03)
[70]   Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT [J].
Lavassani, Mehrzad ;
Forsstrom, Stefan ;
Jennehag, Ulf ;
Zhang, Tingting .
SENSORS, 2018, 18 (05)