Smart Wearable System for Safety-Related Industrial IoT Applications

2018 ◽  
pp. 154-164
Author(s):  
Ali Hayek ◽  
Samer Telawi ◽  
Johannes Klos ◽  
Josef Börcsök ◽  
Roy Abi Zeid Daou
Keyword(s):  
Wearable System ◽  
Iot Applications ◽  
Industrial Iot ◽  
Smart Wearable

Internet of things-based smart wearable system to monitor sports person health

2021 ◽  
pp. 1-14
Author(s):  
Fen Li ◽  
Oscar Sanjuán Martínez ◽  
R.S. Aiswarya
Keyword(s):  
Internet Of Things ◽  
Experimental Result ◽  
Wearable System ◽  
Wearable Systems ◽  
Trading Decisions ◽  
Time Basis ◽  
And Performance ◽  
Individual Sports ◽  
Smart Wearable ◽  
The Internet Of Things

BACKGROUND: The modern Internet of Things (IoT) makes small devices that can sense, process, interact, connect devices, and other sensors ready to understand the environment. IoT technologies and intelligent health apps have multiplied. The main challenges in the sports environment are playing without injuries and healthily. OBJECTIVE: In this paper the Internet of Things-based Smart Wearable System (IoT-SWS) is introduced for monitoring sports person activity to improve sports person health and performance in a healthy way. METHOD: Wearable systems are commonly used to capture individual sports details on a real-time basis. Collecting data from wearable devices and IoT technologies can help organizations learn how to optimize in-game strategies, identify opponents’ vulnerabilities, and make smarter draft choices and trading decisions for a sportsperson. RESULTS: The experimental result shows that IoT-SWS achieve the highest accuracy of 98.22% and efficient in predicting the sports person’s health to improve sports person performance reliably.

A Smart Wearable System To Manage Anxiety Of College Students

2021 ◽  
Author(s):  
Jimmy Armas ◽  
Carlos Gerald Angeles La Torre ◽  
Dennis Armando Angeles La Torre ◽  
Paola A. Gonzalez
Keyword(s):  
College Students ◽  
Wearable System ◽  
Smart Wearable

Role of machine learning and deep learning in securing 5G-driven industrial IoT applications

2021 ◽  
pp. 102685
Author(s):  
Parjanay Sharma ◽  
Siddhant Jain ◽  
Shashank Gupta ◽  
Vinay Chamola
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Iot Applications ◽  
Industrial Iot

Machine Learning for Industrial IoT Systems

2021 ◽  
pp. 336-358
Author(s):  
Mona Bakri Hassan ◽  
Elmustafa Sayed Ali Ahmed ◽  
Rashid A. Saeed
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Operations Management ◽  
Industrial Applications ◽  
Smart Devices ◽  
Iot Applications ◽  
Industrial Iot ◽  
Effective Decision ◽  
Effective Decision Making

The use of AI algorithms in the IoT enhances the ability to analyse big data and various platforms for a number of IoT applications, including industrial applications. AI provides unique solutions in support of managing each of the different types of data for the IoT in terms of identification, classification, and decision making. In industrial IoT (IIoT), sensors, and other intelligence can be added to new or existing plants in order to monitor exterior parameters like energy consumption and other industrial parameters levels. In addition, smart devices designed as factory robots, specialized decision-making systems, and other online auxiliary systems are used in the industries IoT. Industrial IoT systems need smart operations management methods. The use of machine learning achieves methods that analyse big data developed for decision-making purposes. Machine learning drives efficient and effective decision making, particularly in the field of data flow and real-time analytics associated with advanced industrial computing networks.

scholarly journals Evaluation of physiological workload assessment methods using heart rate and accelerometry for a smart wearable system

Ergonomics ◽  
2019 ◽  
Vol 62 (5) ◽  
pp. 694-705 ◽  
Author(s):  
Liyun Yang ◽  
Ke Lu ◽  
Mikael Forsman ◽  
Kaj Lindecrantz ◽  
Fernando Seoane ◽  
...  
Keyword(s):  
Heart Rate ◽  
Assessment Methods ◽  
Wearable System ◽  
Smart Wearable
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