Adaptive deep convolutional neural network‐based secure integration of fog to cloud supported Internet of Things for health monitoring system

2020 ◽  
Vol 31 (10) ◽  
Author(s):  
Revathi Kesavan ◽  
Samydurai Arumugam
Keyword(s):  
Neural Network ◽  
Internet Of Things ◽  
Convolutional Neural Network ◽  
Monitoring System ◽  
Health Monitoring ◽  
Deep Convolutional Neural Network ◽  
Health Monitoring System

scholarly journals Simplified-Boost Reinforced Model-Based Complex Wind Signal Forecasting

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Qiushuang Lin ◽  
Chunxiang Li ◽  
Chao Wu
Keyword(s):  
Neural Network ◽  
Structural Health Monitoring ◽  
Convolutional Neural Network ◽  
Monitoring System ◽  
High Precision ◽  
Health Monitoring ◽  
Wind Engineering ◽  
Stage Model ◽  
Health Monitoring System ◽  
Non Gaussian

Wind signal forecasting has become more and more crucial in the structural health monitoring system and wind engineering recently. It is a challenging subject owing to the complicated volatility of wind signals. The robustness and generalization of a predictor are significant as well as of high precision. In this paper, an adaptive residual convolutional neural network (CNN) is developed, aiming at achieving not only high precision but also high adaptivity for various wind signals with varying complexity. Afterwards, reinforced forecasting is adopted to enhance the robustness of the preliminary forecasting. The preliminary forecast results by adaptive residual CNN are integrated with historical observed signals as the new input to reconstruct a new forecasting mapping. Meanwhile, simplified-boost strategy is applied for more generalized results. The results of multistep forecasting for five kinds of nonstationary non-Gaussian wind signals prove the more excellent adaptivity and robustness of the developed two-stage model compared with single models.

An elderly health monitoring system based on biological and behavioral indicators in internet of things

2020 ◽  
Author(s):  
Mehdi Hosseinzadeh ◽  
Jalil Koohpayehzadeh ◽  
Marwan Yassin Ghafour ◽  
Aram Mahmood Ahmed ◽  
Parvaneh Asghari ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Health Monitoring ◽  
Behavioral Indicators ◽  
Health Monitoring System ◽  
Elderly Health

scholarly journals A Detailed Research on Human Health Monitoring System Based on Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lei Ru ◽  
Bin Zhang ◽  
Jing Duan ◽  
Guo Ru ◽  
Ashutosh Sharma ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Human Health ◽  
Monitoring System ◽  
Health Monitoring ◽  
Health Management ◽  
The Internet ◽  
Health Monitoring System ◽  
Physiological Information ◽  
Public And Private Sector ◽  
The Internet Of Things

The technological advent in smart sensing devices and the Internet has provided practical solutions in various sectors of networking, public and private sector industries, and government organizations worldwide. This study intends to combine the Internet of Things (IoT) technology with health monitoring to make it personalized and timely through allowing the interconnection between the devices. This work is aimed at exploring various wearable health monitoring modules that people wear to monitor heart rate, blood pressure, pulse, body temperature, and physiological information. The information is acquired using the wireless sensor to create a health monitoring system. The data is integrated using the Internet of Things for processing, connecting, and computing to achieve real-time monitoring. The temperature of three people measured by the temperature thermometer is 36.4, 36.7, and 36.5 (°C), respectively, and the average acquired by the monitoring system of the three people is 36.5, 36.4, and 36.5 (°C), respectively, indicating that the system demonstrated relatively accurate and stable testability. The user’s ECG is displayed clearly and conveniently using the ECG acquisition system. The pulse rate of the three people tested by the system is 78, 78, and 79 (times/min), respectively, similar to the medical pulse meter results. The physiological information acquired using the semantic recognition, matching system, and character matching system is relatively accurate. It concludes that the human health monitoring system based on the Internet of Things can provide people with daily health management, instrumental in heightening health service quality and level.

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