Development of Decision Support System for Health Care Consultation using RFID Based NFC Tags for Patient Identification

Zaffar, Arshia; Gul, Mahnoor; Mumtaz, Rida; Khan, Amir Azam

doi:10.5815/ijieeb.2016.03.03

Cited by 4 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, we should note that the RF harmonic transponder could also include the energy-efficient radio frequency identification (RFID) chip with memory and the backscatter transistor such that identification can be performed along with sensing. − The ID data path is picked up by the RFID reader, so the proposed smart face mask can be either used as a pure sensor (chipless) or sensor with ID (chip-enabled) underneath the standard RFID operating protocols. In addition, the recorded cough events, including the amplitude and number of peaks in the time-domain data (Figures and ), can be analyzed using intelligent algorithms, such as machine learning and deep learning methods, − for recognizing features (e.g., dry cough, productive wet cough, or chesty cough) that correspond to different respiratory diseases.…”

Section: Results and Discussionmentioning

confidence: 99%

A Breathable, Reusable, and Zero-Power Smart Face Mask for Wireless Cough and Mask-Wearing Monitoring

Ling

Yang

et al. 2022

ACS Nano

View full text Add to dashboard Cite

We herein introduce a lightweight and zero-power smart face mask, capable of wirelessly monitoring coughs in real time and identifying proper mask wearing in public places during a pandemic. The smart face mask relies on the compact, battery-free radio frequency (RF) harmonic transponder, which is attached to the inner layer of the mask for detecting its separation from the face. Specifically, the RF transponder composed of miniature antennas and passive frequency multiplier is made of spray-printed silver nanowires (AgNWs) coated with a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) passivation layer and the recently discovered multiscale porous polystyrene-block-poly(ethylene-ran-butylene)-block-polystyrene (SEBS) substrate. Unlike conventional on-chip or on-board wireless sensors, the SEBS-AgNWs/PEDOT:PSS-based RF transponder is lightweight, stretchable, breathable, and comfortable. In addition, this wireless device has excellent resilience and robustness in long-term and repeated usages (i.e., repeated placement and removal of the soft transponder on the mask). We foresee that this wireless smart face mask, providing simultaneous cough and mask-wearing monitoring, may mitigate virus-transmissive events by tracking the potential contagious person and identifying mask-wearing conditions. Moreover, the ability to wirelessly assess cough frequencies may improve diagnosis accuracy for dealing with several diseases, such as chronic obstructive pulmonary disease.

show abstract

Section: Results and Discussionmentioning

confidence: 99%

A Breathable, Reusable, and Zero-Power Smart Face Mask for Wireless Cough and Mask-Wearing Monitoring

Ling

Yang

et al. 2022

ACS Nano

View full text Add to dashboard Cite

show abstract

“…One is an integrated circuit for storing and processing information, modulating and de-modulating a radio-frequency (RF) signal, and other specialized functions. The second is an antenna for receiving and transmitting the signal.This Technology can be used in various applications [21][22] which involve tracking and monitoring of objects provided with unique identification number e.g. patient monitoring, vehicle tracking in toll path, objects tracking in supply chain etc.…”

mentioning

confidence: 99%

“…This Technology can be used in various applications [21][22] which involve tracking and monitoring of objects provided with unique identification number e.g. patient monitoring, vehicle tracking in toll path, objects tracking in supply chain etc.…”

mentioning

confidence: 99%

Predictive Analysis of RFID Supply Chain Path Using Long Short Term Memory (LSTM): Recurrent Neural Networks

Sharma¹,

Tomer²

2018

IJWMT

View full text Add to dashboard Cite

Prediction of location has gained lot of attention in different applications areas like predicting the path or any deviation like taxi-route, bus route, human trajectory, robot navigation. Prediction of the next location or any path deviation in RFID enabled supply chain path followed in the process is quite a novel area for the related techniques. The paper defines the architecture for the outlier detection in RFID enabled Supply Chain Path based on historical datasets .Given the training datasets, different classification models are compared for the accurate prediction of the outlierness of the path followed by the tagged objects read by RFID readers during the supply chain process. Comparison of Hidden Markov Model(HMM), XGBoost(decision tree based boosting),Recurrent Neural Network(RNN) and state of art technique in RNN known as Long Short Term Memory (LSTM) is done .To our knowledge LSTM has never been used for this application area for outlier prediction. For the longer path sequences, LSTM has outperformed over other techniques. The training datasets used here are in the form of the record of the outlier positions in particular path and at particular time and location. 67 Memory (LSTM): Recurrent Neural Networks really helpful for long distance automatic sensing/reading/identification of any tagged object, person or package within readers 'range. This is done using RFID tags. These are small transponders which consist of radio receiver and transmitter to transmit identity information over a distance, when asked. RFID tag reader is used to read the tag using radio waves. The readers are connected to computer systems to record the data read from the tagged object. Most RFID tags contain at least two parts. One is an integrated circuit for storing and processing information, modulating and de-modulating a radio-frequency (RF) signal, and other specialized functions. The second is an antenna for receiving and transmitting the signal.This Technology can be used in various applications [21][22] which involve tracking and monitoring of objects provided with unique identification number e.g. patient monitoring, vehicle tracking in toll path, objects tracking in supply chain etc. In this paper tracking and monitoring of RFID tagged objects or group of objects with unique electronic product code (EPC) in supply chain path is discussed. It starts with the brief introduction RFID enabled supply chain process, then explanation of the pre processing and feature extraction from the raw data read by the readers. Various classification techniques are compared for the predictive modelling.

show abstract

Analysis of evaluation quality website from developers perspective for build website

Rahayu¹,

Utami²,

Luthfi³

2018

2018 International Conference on Information and Communications Technology (ICOIACT)

View full text Add to dashboard Cite

Development of Decision Support System for Health Care Consultation using RFID Based NFC Tags for Patient Identification

Cited by 4 publications

References 2 publications

A Breathable, Reusable, and Zero-Power Smart Face Mask for Wireless Cough and Mask-Wearing Monitoring

A Breathable, Reusable, and Zero-Power Smart Face Mask for Wireless Cough and Mask-Wearing Monitoring

Predictive Analysis of RFID Supply Chain Path Using Long Short Term Memory (LSTM): Recurrent Neural Networks

Analysis of evaluation quality website from developers perspective for build website

Contact Info

Product

Resources

About