Research Article
Anomaly Detection Method of Healthcare Internet of Things Gateway Supporting Edge Computing
@INPROCEEDINGS{10.1007/978-3-031-33545-7_17, author={Zixiu Zou and Yi Hu and Xinyao Liu and Shufeng Zhuo}, title={Anomaly Detection Method of Healthcare Internet of Things Gateway Supporting Edge Computing}, proceedings={IoT and Big Data Technologies for Health Care. Third EAI International Conference, IoTCare 2022, Virtual Event, December 12-13, 2022, Proceedings}, proceedings_a={IOTCARE}, year={2023}, month={5}, keywords={Edge Calculation Medical Care Internet Of Things Gateway Is Abnormal Test Method}, doi={10.1007/978-3-031-33545-7_17} }- Zixiu Zou
Yi Hu
Xinyao Liu
Shufeng Zhuo
Year: 2023
Anomaly Detection Method of Healthcare Internet of Things Gateway Supporting Edge Computing
IOTCARE
Springer
DOI: 10.1007/978-3-031-33545-7_17
Abstract
As the link between the perception layer and the network layer, the Internet of Things gateway is of great significance to the safe and stable operation of the healthcare Internet of Things. Once the gateway is abnormal, it will directly affect the information transmission in health care work. Therefore, an anomaly detection method for the gateway of the Internet of Things in health care supporting edge computing is proposed. Several representative gateway status indicators are selected by using the maximum uncorrelation method, and the gateway anomaly detection task is unloaded to the edge server by using edge computing. An anomaly detection model based on SOFM neural network and random forest is constructed to realize the anomaly detection of the Internet of Things gateway in health care. The experimental results show that the determination coefficients of the six types of samples of this method are more than 0.9, which is close to 1, which shows that this method has better anomaly detection performance of the Internet of Things gateway in health care.
