TY - CHAP
T1 - Edge intelligence case study on medical Internet of Things security
AU - Feng, Xiaohua
N1 - Publisher Copyright:
© 2023 Elsevier Inc. All rights reserved.
PY - 2023/6/5
Y1 - 2023/6/5
N2 - MIoT (Medical Internet of Things) systems produced many of sensing data in the world. Consequently, there is a demand of scientific research in this field. Edge intelligence fit in this trends, as one of the developing cutting-edge technology. A systematic approach had been applied on the health informatics edge intelligence devices’ investigation. The observing and recording action that occurs in the process of this research to date had been satisfed. This work had been reported here. The analyzing of the case study data was carried out. Eventually, some results have been summarized based on the investigation. Furthermore, a solution is proposed for the kind of medical edge intelligence device data cyber security problem-solving.
Edge intelligence was defined as “the devices available at the edge layer have some limited amount of computing resource which can be utilized and incorporated with machine learning or AI (Artificial intelligence) algorithms to perform RT (real time) data analytics”. Studying more in the category of edge intelligence would influence MIoT system. This survey on edge intelligence had been carried out on investigated recent MIoT, Robot, Raspberry Pi and AV (autonomous vehicle) and so on as edge terminal - edge intelligence devices and the challenges they had encounter. In particular, AI application in edge intelligence device handle medical data security threat. AI face more challenges in edge intelligence computing. In this survey, through some case studies, some advantages and disadvantages had been studied. MIoT edge intelligence device challenges on big data security issues had been discussed.
AB - MIoT (Medical Internet of Things) systems produced many of sensing data in the world. Consequently, there is a demand of scientific research in this field. Edge intelligence fit in this trends, as one of the developing cutting-edge technology. A systematic approach had been applied on the health informatics edge intelligence devices’ investigation. The observing and recording action that occurs in the process of this research to date had been satisfed. This work had been reported here. The analyzing of the case study data was carried out. Eventually, some results have been summarized based on the investigation. Furthermore, a solution is proposed for the kind of medical edge intelligence device data cyber security problem-solving.
Edge intelligence was defined as “the devices available at the edge layer have some limited amount of computing resource which can be utilized and incorporated with machine learning or AI (Artificial intelligence) algorithms to perform RT (real time) data analytics”. Studying more in the category of edge intelligence would influence MIoT system. This survey on edge intelligence had been carried out on investigated recent MIoT, Robot, Raspberry Pi and AV (autonomous vehicle) and so on as edge terminal - edge intelligence devices and the challenges they had encounter. In particular, AI application in edge intelligence device handle medical data security threat. AI face more challenges in edge intelligence computing. In this survey, through some case studies, some advantages and disadvantages had been studied. MIoT edge intelligence device challenges on big data security issues had been discussed.
KW - Medical Internet of Things
KW - MIoT (Medical Internet of Things)
KW - ML (machine learning) and DL (deep learning)
KW - Security and forensics
KW - Information security
KW - Big data analytics
KW - Healthcare informatics
KW - Robot
KW - Edge intelligence
UR - https://www.scopus.com/pages/publications/85194186668
U2 - 10.1016/B978-0-323-99421-7.00003-9
DO - 10.1016/B978-0-323-99421-7.00003-9
M3 - Chapter
SN - 9780323994217
T3 - Advances in ubiquitous sensing applications for healthcare
SP - 227
EP - 245
BT - Computational Intelligence for Medical Internet of Things (MIoT) Applications
A2 - Maleh, Yassine
A2 - Abd El-latif, Ahmed A.
A2 - Curran, Kevin
A2 - Siarry, Patrick
PB - Elsevier B.V.
ER -