Soft electronic material based sensor with optical network in sports application for player movement analysis using machine learning model DOI
Jingyi Wu

Optical and Quantum Electronics, Journal Year: 2024, Volume and Issue: 56(4)

Published: Jan. 30, 2024

Language: Английский

AI- and IoT-Assisted Sustainable Education Systems during Pandemics, such as COVID-19, for Smart Cities DOI Open Access
M. M. Kamruzzaman, Saad Alanazi, Madallah Alruwaili

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(10), P. 8354 - 8354

Published: May 21, 2023

The integration of AI and the IoT in education has potential to revolutionize way we learn. Personalized learning, real-time feedback support, immersive learning experiences are some benefits that can bring system. In this regard, research paper aims investigate how be integrated into sustainable order provide students with personalized during pandemics, such as COVID-19, for smart cities. study’s key findings report employed through learning. AI-powered algorithms used analyze student data create each student. This includes providing tailored content, assessments, align their unique style pace. Additionally, communicate a more natural human-like way, making experience engaging interactive. Another aspect obtained from is ability support. IoT-enabled devices, cameras microphones, monitor engagement feedback. then use these adapt real time. tablets laptops, collect process work, allowing automatic grading assignments assessments. technology facilitate remote monitoring which would particularly useful who cannot attend traditional classroom settings. Furthermore, also intelligent personal environments (PLEs) personalized, adaptive, experiences. combined algorithms, PLE student’s needs preferences. It concluded integrating people learn, support opening up new opportunities disadvantaged students. However, it will important ensure ethical responsible all have equal access technologies.

Language: Английский

Citations

48

Survey on Sensors and Smart Devices for IoT Enabled Intelligent Healthcare System DOI Open Access
Swati Chopade, Hari Prabhat Gupta, Tanima Dutta

et al.

Wireless Personal Communications, Journal Year: 2023, Volume and Issue: 131(3), P. 1957 - 1995

Published: June 12, 2023

Language: Английский

Citations

30

IoT Applications in Sports and Fitness: Enhancing Performance Monitoring and Training DOI
Ramakrishnan Raman, Meenakshi Kaul, Meenakshi Ravindran

et al.

Published: Aug. 18, 2023

IoT (IoT) has transformed sports, fitness, and more. This article discusses in sports wellness performance monitoring preparation. Wearables, sensors, data analytics help athletes, coaches, fitness enthusiasts gather, analyze, use real-time data. Training may improve, reducing injuries performance. covers applications covering necessary improvements their implications on checking Smartwatches, trackers biometric sensors record signs, movement patterns, physiological It also analyzes how IoT-enabled devices broadcast data, enabling athletes trainers to monitor assess indicators make decisions remotely. research investigates systems analytics. Predictive models machine learning algorithms can analyze enormous volumes of find provide personalized advice enhance training. explores VR AR might be utilized with create realistic, interactive teaching environments. Data privacy security protect sensitive personal information. highlights revolutionize the game. assist training, performing, analyzing will change it screens, train, succeed proactive health.

Language: Английский

Citations

30

Artificial Intelligence in Physical Education DOI
Jumel C. Miller, John Paul P. Miranda, Julius Ceazar G. Tolentino

et al.

Advances in educational technologies and instructional design book series, Journal Year: 2024, Volume and Issue: unknown, P. 37 - 60

Published: Sept. 6, 2024

Artificial intelligence (AI) has emerged as a transformative force impacting various domains, including education. Within the context of physical education, AI presents innovative solutions and opportunities that have potential to transform traditional instructional assessment methodologies. The primary objective this chapter is critically examine integration technologies within education explore how they enhance both methods evaluation processes. This review provides comprehensive overview evolving landscape by analyzing common research designs, key specific applications in Furthermore, it highlights significant role personalized learning performance optimization, enabling more tailored feedback support for students. also explores AI-driven advancements quality assessment, course recommendations, teacher development, classroom technologies.

Language: Английский

Citations

9

Transforming Education with the Internet of Things: A Journey into Smarter Learning Environments DOI Open Access
Ruşen Meylani

International Journal of Research in Education and Science, Journal Year: 2024, Volume and Issue: 10(1), P. 161 - 178

Published: Feb. 17, 2024

This review explores the integration and effects of Internet Things (IoT) in education, highlighting its importance transforming traditional teaching learning techniques. It examines early uses historical growth IoT, development, turning points adoption. IoT platforms, tools, technologies including wearables, smart devices, augmented virtual reality, gamification, collaborative learning. discusses role improving campus management, intelligent campuses with IoT-enabled infrastructure, energy-saving technologies, safety security improvements. The study data privacy issues installations ethical legal implications collection classroom. also upcoming trends prospects for usage AI machine integration. Finally, provides insights educators, decision-makers, stakeholders, identifying research gaps recommending areas future implementation.

Language: Английский

Citations

7

Effects of digital monitoring and immediate feedback on physical activity and fitness in undergraduates DOI
Xu Li, Wee Hoe Tan, X Zheng

et al.

Education and Information Technologies, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 24, 2024

Language: Английский

Citations

5

Creating IoT-Enriched Learner-Centered Environments in Sports Science Higher Education during the Pandemic DOI Open Access
Rocsana Bucea-Manea-Țoniș,

Luciela Vasile,

Rareș Stănescu

et al.

Sustainability, Journal Year: 2022, Volume and Issue: 14(7), P. 4339 - 4339

Published: April 6, 2022

In the pandemic context, creating IoT-enriched learner-centered environments was not only a tendency but requirement for sustainable teaching and learning in universities with sports science programs theoretical classes practical activities. Our study aims to assess both extent which academic environment has been prepared online key features of dedicated e-learning training provide highest-quality educational services conditions. An survey administered staff field from two Romanian universities. The results reveal that associated major changes terms methods methodology, also new dynamic external internal factors regarding teachers their relationship students. At same time, it depends on solid specific infrastructure IoT facilities (MOOCs, VR/AR, mobile devices). As mirror student-centered approach, have experienced concerns about outcomes process. this regard, can become if they positively integrate into system consolidate quality standards an perspective.

Language: Английский

Citations

20

Meta learning-based few-shot intrusion detection for 5G-enabled industrial internet DOI Creative Commons
Yan Yu, Yang Yu, Fang Shen

et al.

Complex & Intelligent Systems, Journal Year: 2024, Volume and Issue: 10(3), P. 4589 - 4608

Published: March 25, 2024

Abstract With the formation and popularization of 5G-enabled industrial internet, cybersecurity risks are increasing, limited number attack samples, such as zero-day, leaves a short response time for security protectors, making it substantially more difficult to protect control systems from new types malicious attacks. Traditional supervised intrusion detection models rely on large samples training their performance needs be improved. Therefore, there is an urgent need few-shot detection. Aiming at above problems, this paper proposes model based meta-learning framework, which aims effectively improve accuracy real-time detection, designs containing sample generation module, feature mapping module metric module. Among them, introduces residual block into Natural GAN method generate high-quality antagonistic samples—Res-Natural GAN, used enhance antagonism generated mining degree, traffic detection; attention mechanism, multi-head fast applied encoder structure transformer combined with parameter optimization algorithm particle swarm mutation shorten while features effectively; prototype storage update combines network achieve correct classification by measuring Euclidean distance between detected class prototypes, inference ensuring accuracy; finally, three modules form model. To evaluate proposed model, five different experiments conducted multiple public datasets. The experimental results show that has higher than traditional both zero-shot attacks, not only applicable but also generalized environments types.

Language: Английский

Citations

4

Using Reinforcement Learning Algorithms to Optimize Practical Skills Development in Higher Vocational and Technical Education DOI Creative Commons
Xingli Zhang

Deleted Journal, Journal Year: 2024, Volume and Issue: 20(6s), P. 2146 - 2155

Published: April 29, 2024

Optimizing practical skills development in higher vocational and technical education involves a multifaceted approach. Firstly, curriculum design should integrate hands-on learning experiences, industry-relevant projects, internships to bridge the gap between theoretical knowledge real-world application. Secondly, institutions invest state-of-the-art facilities, equipment, technology provide students with simulated work environment conducive skill mastery. This paper, explored integration of reinforcement algorithms within Seahorse Optimization Probability Education (SHOPE) framework optimize education. Through extensive experimentation analysis, we investigate effectiveness various enhancing teaching strategies, assessment processes, classification tasks educational contexts. Our findings highlight capability SHOPE iteratively refine methodologies, leading significant improvements student acquisition, success rates, accuracy over multiple epochs. With adaptive optimized programs tailored individual needs. For instance, our results demonstrate an average improvement ranging from 35% 65% across different algorithms. Moreover, rates for mastering targeted reach levels 75% 92%.

Language: Английский

Citations

4

Enhancing college students physical education using artificial intelligence-optimized teaching system based on biomechanics DOI Open Access
Zixuan Gao, Hongjing Guan,

Tan Zhi

et al.

Molecular & cellular biomechanics, Journal Year: 2025, Volume and Issue: 22(2), P. 503 - 503

Published: Jan. 17, 2025

Physical Education Teaching concerns the process of leading students to perform different tasks, games, and workouts that improve physical fitness, body control, health. In realm cell molecular biomechanics, education teaching can be regarded as a means induce specific physiological responses at microscopic level. The various activities in which partake, like diverse tasks workouts, exert mechanical forces permeate throughout impinge upon cells tissues. During exertion, within muscles, bones, connective tissues are subject biomechanical stress. This stress triggers cascade events. Teachers focus on enhancing spatial manual skills, promoting cooperation, setting up priorities. this research, it is proposed learn about system colleges universities using artificial intelligence (AI) optimization algorithm. Thus, for predicting achievements college education, we propose Blue Monkey optimization-driven Weight-Tuned AdaBoost (BM-WTAdaBoost) observations variables were derived from typical programs during their training sessions. A data pre-processing technique known min–max normalization applied obtained raw enhance its quality. For nonlinear data, Kernel Principal Component Analysis (kernel-PCA) employed helps extracting information, turn making accurate predictions. following our model: BM opt with WTAdaBoost selecting features model accuracy students’ outcomes. Python program uses suggested technique. finding assessment phase assesses model’s prediction efficacy several measures, including ratio (99.8%), F1-score (95.56%), (98.24%), interaction (97.2%), efficiency performance error rate (5.62%). We also performed comparative analysis traditional approaches assess strategy. Comparative methods shows superiority approach outcomes considering providing novel perspective understanding optimizing relation biological world.

Language: Английский

Citations

0