Orientation Training System for Elders with Dementia Using Internet of Things

Author(s):  
Lun-Ping Hung ◽  
Chien-Liang Chen ◽  
Chien-Ting Sung ◽  
Chia-Ling Ho
2021 ◽  
pp. 1-11
Author(s):  
Xin Xie

With the emergence of the Internet of Things technology and the rapid development of computer technology and network communication technology, a profound technological change is taking place in the education model. Based on the current problems in the teaching of computer network courses and the improvement needs of the innovative computer training platform of the Internet of Multiple Intelligences, this article summarizes the ideas for improving the innovative computer training platform of the Internet of Multiple Intelligences of the computer network, and explores the mobile learning environment of computer network courses. Based on the multi-level feedback teaching mode, each type of experiment in the innovative computer training system is divided into theoretical tests, basic experiments, improved experiments and inquiry experiments. After each level is completed, the problem will be fed back to the teacher through the system, the results and suggestions will be fed back to the students, and the students will increase their interest in learning, improve the performance of innovative computer training, cultivate the students’ ability to explore and innovate, and help teachers to grasp the students’ innovation in computer training. This article demonstrates the teaching effect of the system through quasi-experimental research methods and interview methods. According to the results of quasi-experimental research and interviews, it is found that this system can improve the teaching effect of teachers, stimulate students’ interest in learning and improve academic performance. The construction and application research of this system will provide support for the construction and practical teaching of an innovative computer training system for the multi-dimensional Internet of Things.


PEDIATRICS ◽  
1994 ◽  
Vol 94 (6) ◽  
pp. 1108-1110
Author(s):  
Abby Shapiro Kendrick

Training in child care assumes a number of forms. There is pre-service training (needed before entering the field); orientation training (received when first on the job, highlighting the most essential skills, tasks and knowledge needed to begin the job); and ongoing training (required by regulation or recommended periodically for current staff). Despite the fact that training is known to have a positive effect on the field of early care and education, the current training system is fraught with problems. A 1991 national survey conducted by the Wheelock College Center for Career Development in Early Care and Education found that at least one of three key informants in 59% of states said "training is fragmented, random, scattershot, and not based on the needs of the field."1 The licensing system requires minimal training and experience. For teachers in child-care centers, five states require no training, four states require pre-service training, 29 states require only ongoing training, and 14 states require both pre-service and ongoing training. Few states require more than 10 hours of annual ongoing training for any child-care professionals. For family child-care providers, the numbers are even lower: 24 states require no training and only 12 states require annual ongoing training.1 If first aid and cardiaopulmonary resuscitation (CPR) certification are required, there is little time for any other training. In addition to limited funds to support training and limited incentives for providers, administrators, on funders to invest in training, other well-known barriers to implementing systematic and coordinated training efforts include the following items:


2021 ◽  
pp. 1-14
Author(s):  
Zhi Fang ◽  
Rajendra Prasad Mahapatra ◽  
P. Selvaraj

BACKGROUND: The Internet of Things (IoT) has recently become a prevalent technological culture in the sports training system. Although numerous technologies have grown in the sports training system domain, IoT plays a substantial role in its optimized health data processing framework for athletes during workouts. OBJECTIVE: In this paper, a Dynamic data processing system (DDPS) has been suggested with IoT assistance to explore the conventional design architecture for sports training tracking. Method: To track and estimate sportspersons physical activity in day-to-day living, a new paradigm has been combined with wearable IoT devices for efficient data processing during physical workouts. Uninterrupted observation and review of different sportspersons condition and operations by DDPS helps to assess the sensed data to analyze the sportspersons health condition. Additionally, Deep Neural Network (DNN) has been presented to extract important sports activity features. RESULTS: The numerical results show that the suggested DDPS method enhances the accuracy of 94.3%, an efficiency ratio of 98.2, less delay of 24.6%, error range 28.8%, and energy utilization of 31.2% compared to other existing methods.


Author(s):  
Yoshikazu SEKI ◽  
Yukio IWAYA ◽  
Takeru CHIBA ◽  
Satoshi YAIRI ◽  
Makoto OTANI ◽  
...  

Author(s):  
Yoshikazu SEKI ◽  
Yukio IWAYA ◽  
Makoto OH-UCHI ◽  
Yo-iti SUZUKI

2021 ◽  
Vol 27 (spe2) ◽  
pp. 62-65
Author(s):  
Jinling Li

ABSTRACT Special physical fitness plays an important role in sports skills, improving athletic performance and preventing injuries. Based on the Internet of Things (IoT), the method of assessing athletes’ specific physical fitness is studied using the linear acceleration energy estimation model. After relevant research on the athletes’ real training environment, a real-time monitoring platform is designed. Besides, the MQVA algorithm is proposed, and the simulation experiment is designed. Finally, the accuracy of several algorithms is verified by the practical method of evaluating the application. The verification results show that the precision of the algorithm and the model achieve the expected results. An evaluation model is proposed for individual athletes of the training effect based on the energy consumption rate; for multi-athletes, the indicators used are the progress of energy transfer. This model is compared and verified employing examples. The results show that the evaluation model is accurate and reliable. This investigation is part of the contents of the investigation of the physical fitness training system of the potential advantage project in China. It can provide a theoretical basis for coaches to adopt effective special physical training approaches and methods.


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