RFID technology in sports competitions timekeeping application

2013 ◽  
Author(s):  
Shanli Yi
Keyword(s):  
Rfid Technology

A Multi-Sensing-Range Method for Efficient Position Estimation by Passive RFID Technology

2009 ◽  
Vol E92-A (10) ◽  
pp. 2609-2617 ◽  
Author(s):  
Toshihiro HORI ◽  
Tomotaka WADA ◽  
Norie UCHITOMI ◽  
Kouichi MUTSUURA ◽  
Hiromi OKADA
Keyword(s):  
Position Estimation ◽  
Rfid Technology ◽  
Sensing Range ◽  
Passive Rfid

Development of the On-board Maintenance Management System for Ground Coils of Maglev by Using RFID Technology

2012 ◽  
Vol 53 (1) ◽  
pp. 46-51
Author(s):  
Minoru TANAKA ◽  
Noriyuki TAKAHASHI ◽  
Masao SUZUKI ◽  
Ryohei IKEDA ◽  
Sei NAGASAKA
Keyword(s):  
Management System ◽  
Maintenance Management ◽  
Rfid Technology

Field Trials of RFID Technology for Tracking Pre-Fabricated Pipe Spools

2004 ◽  
Author(s):  
Jongchul Song ◽  
Carlos Caldas ◽  
Esin Ergen ◽  
Carl Haas ◽  
Burcu Akinci
Keyword(s):  
Field Trials ◽  
Rfid Technology

Automation System for Six-minute Walk Test Using RFID Technology

2020 ◽  
Author(s):  
Vinicius Oliveira ◽  
Lucas Duarte ◽  
Gabriel Costa ◽  
Marcielly Macedo ◽  
Tagleorge Silveira
Keyword(s):  
Automation System ◽  
Walk Test ◽  
Rfid Technology ◽  
Six Minute Walk Test ◽  
Minute Walk

scholarly journals Smart Gateless System using RFID Technology in Universiti Malaysia Perlis

2021 ◽  
Vol 1878 (1) ◽  
pp. 012066
Author(s):  
A F M Fazilah ◽  
M Jusoh ◽  
A Zakaria ◽  
T Sabapathy ◽  
M F Ibrahim ◽  
...  
Keyword(s):  
Rfid Technology

scholarly journals Remote Patient Monitoring Using Radio Frequency Identification (RFID) Technology and Machine Learning for Early Detection of Suicidal Behaviour in Mental Health Facilities

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 776
Author(s):  
Xiaohui Tao ◽  
Thanveer Basha Shaik ◽  
Niall Higgins ◽  
Raj Gururajan ◽  
Xujuan Zhou
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Radio Frequency Identification ◽  
Patient Monitoring ◽  
Vital Signs ◽  
Remote Patient Monitoring ◽  
Rfid Technology ◽  
Rpm System ◽  
Frequency Identification ◽  
Remote Patient

Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient’s daily activities and can enhance the efficiency of healthcare delivery in acute clinical settings. In this study, an RPM system was built using radio frequency identification (RFID) technology for early detection of suicidal behaviour in a hospital-based mental health facility. A range of machine learning models such as Linear Regression, Decision Tree, Random Forest, and XGBoost were investigated to help determine the optimum fixed positions of RFID reader–antennas in a simulated hospital ward. Empirical experiments showed that Decision Tree had the best performance compared to Random Forest and XGBoost models. An Ensemble Learning model was also developed, took advantage of these machine learning models based on their individual performance. The research set a path to analyse dynamic moving RFID tags and builds an RPM system to help retrieve patient vital signs such as heart rate, pulse rate, respiration rate and subtle motions to make this research state-of-the-art in terms of managing acute suicidal and self-harm behaviour in a mental health ward.

scholarly journals A Model of the Environmental Burden of RFID Technology in the Slovak Republic

2021 ◽  
Vol 13 (7) ◽  
pp. 3684
Author(s):  
Bibiana Bukova ◽  
Jiri Tengler ◽  
Eva Brumercikova
Keyword(s):  
Radio Frequency Identification ◽  
Slovak Republic ◽  
Electronic Waste ◽  
Rfid Tags ◽  
Rfid Technology ◽  
Environmental Burden ◽  
The Core ◽  
Regulatory Approach ◽  
Frequency Identification ◽  
Model Household

The paper focuses on the environmental burden created by Radio Frequency Identification (RFID) tags in the Slovak Republic (SR). In order to determine the burden there, a model example was created to calculate electronic waste produced by households in the SR by placing RFID tags into municipal waste. The paper presents a legislative regulatory approach towards the environmental impacts from using RFID tags in the SR, as well as an analysis of the environmental burden of using RFID tags throughout the world. The core of the paper is focused on the research conducted in order to calculate the environmental burden of a model household in the SR, where the number of used RFID tags per year was observed; then, the volume of e-waste produced by households of the Slovak Republic per year was determined. In the conclusion, we provide the results of the research presented and discuss including our own proposal for solving the problems connected with the environmental burden of RFID technology.

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