A Novel Approach for RFID Data Cleansing Based on Bayesian Inference

2014 ◽  
Vol 577 ◽  
pp. 856-859
Author(s):  
Fan Yang ◽  
Long Zhang Liu ◽  
Xing Jia Lu
Keyword(s):  
Bayesian Inference ◽  
Data Collection ◽  
Radio Frequency Identification ◽  
System Performance ◽  
Data Cleaning ◽  
Data Redundancy ◽  
Detection Model ◽  
Novel Approach ◽  
State Detection ◽  
Frequency Identification

Radio Frequency Identification (RFID) technologies are used in many applications for data collection. However, raw RFID readings are usually of low quality and may contain many anomalies. The solution should take advantage of the resulting data redundancy for data cleaning. In this paper we propose a Bayesian inference based approach for cleaning RFID raw data. Our approach takes full advantage of data redundancy. To capture the likelihood, we design a 3-state detection model and formally prove this model can maximize the system performance.

Chipless RFID Sensor for High Voltage Condition Monitoring

2012 ◽  
pp. 304-333
Author(s):  
Emran Md Amin ◽  
Nemai Chandra Karmakar
Keyword(s):  
Condition Monitoring ◽  
High Voltage ◽  
Radio Frequency Identification ◽  
Low Cost ◽  
Base Station ◽  
Novel Approach ◽  
Frequency Identification ◽  
On Line ◽  
Passive Rfid ◽  
Passive Circuit

A novel approach for non-invasive radiometric Partial Discharge (PD) detection and localization of faulty power apparatuses in switchyards using Chipless Radio Frequency Identification (RFID) based sensor is presented. The sensor integrates temperature sensing together with PD detection to assist on-line automated condition monitoring of high voltage equipment. The sensor is a multi-resonator based passive circuit with two antennas for reception of PD signal from the source and transmission of the captured PD to the base station. The sensor captures PD signal, processes it with designated spectral signatures as identification data bits, incorporates temperature information, and retransmits the data with PD signals to the base station. Analyzing the PD signal in the base station, both the PD levels and temperature of a particular faulty source can be retrieved. The prototype sensor was designed, fabricated, and tested for performance analysis. Results verify that the sensor is capable of identifying different sources at the events of PD. The proposed low cost passive RFID based PD sensor has a major advantage over existing condition monitoring techniques due to its scalability to large substations for mass deployment.

Agricultural Data Mining in the 21st Century

2010 ◽  
pp. 229-246
Author(s):  
E. Arlin Torbett ◽  
Tanya M. Candia
Keyword(s):  
Public Health ◽  
Data Mining ◽  
Data Collection ◽  
Radio Frequency Identification ◽  
Fresh Produce ◽  
Online Marketing ◽  
Current State ◽  
Working Together ◽  
Frequency Identification ◽  
Rich Information

Data on the production, sale, repackaging, and transportation of fresh produce is scarce, yet with recent threats to national safety and security, forward and backward traceability of produce is mandatory. Recent advances in online marketing of fresh produce, a new international codification system and use of advanced technologies such as Radio Frequency Identification (RFID) and bar coding are working together to fill the gap, building a solid database of rich information that can be mined. While agricultural data mining holds much promise for farmers, with better indications of what and when to plant, and for buyers, giving them access to improved food quality and availability information, it is the world’s health organizations and governments who stand to be the biggest beneficiaries. This chapter describes the current state of fresh produce data collection and access, new trends that fill important gaps, and emerging methods of mining fresh produce data for improved production, product safety and public health through traceability.

Radio Frequency Identification Tagging: A Novel Approach to Monitoring Surface and Subterranean Insects

2011 ◽  
Vol 57 (2) ◽  
pp. 86-93 ◽  
Author(s):  
D. E. Silcox ◽  
J. P. Doskocil ◽  
C. E. Sorenson ◽  
R. L. Brandenburg
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Novel Approach ◽  
Frequency Identification

Intelligent Agents Framework for RFID Hospitals

2010 ◽  
pp. 265-278
Author(s):  
Masoud Mohammadian ◽  
Ric Jentzsch
Keyword(s):  
Data Collection ◽  
Data Acquisition ◽  
Radio Frequency Identification ◽  
Intelligent Agents ◽  
Medical Data ◽  
Time Data ◽  
Raw Data ◽  
Privacy Issue ◽  
Real Time Data ◽  
Frequency Identification

When dealing with human lives, the need to utilize and apply the latest technology to help in saving and maintaining patients’ lives is quite important and requires accurate, near-real-time data acquisition and evaluation. At the same time, the delivery of a patient’s medical data needs to be as fast and as secure as possible. One possible way to achieve this is to use a wireless framework based on radio-frequency identification (RFID). This framework can integrate wireless networks for fast data acquisition and transmission while maintaining the privacy issue. This chapter discusses the development of an agent framework in which RFID can be used for patient data collection. The chapter presents a framework for the knowledge acquisition of patient and doctor profiling in a hospital. The acquisition of profile data is assisted by a profiling agent that is responsible for processing the raw data obtained through RFID and a database of doctors and patients.

scholarly journals Discovery of Characteristic Patterns from Transactions with Their Classes

2012 ◽  
Vol 2012 ◽  
pp. 1-12
Author(s):  
Shigeaki Sakurai
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Numerical Experiments ◽  
New Method ◽  
Minimum Support ◽  
Frequency Identification ◽  
The Difference

This paper deals with transactions with their classes. The classes represent the difference of conditions in the data collection. This paper redefines two kinds of supports: characteristic support and possible support. The former one is based on specific classes assigned to specific patterns. The latter one is based on the minimum class in the classes. This paper proposes a new method that efficiently discovers patterns whose characteristic supports are larger than or equal to the predefined minimum support by using their possible supports. Also, this paper verifies the effect of the method through numerical experiments based on the data registered in the UCI machine learning repository and the RFID (radio frequency identification) data collected from two apparel shops.

Data Management Issues in RFID Applications

2015 ◽  
pp. 179-198 ◽  
Author(s):  
A. Anny Leema ◽  
M. Hemalatha
Keyword(s):  
Radio Frequency Identification ◽  
Data Cleaning ◽  
Hybrid Approach ◽  
Radio Waves ◽  
Quality Of Data ◽  
Resultant Data ◽  
Rfid Data ◽  
Frequency Identification ◽  
Rfid Applications

Radio Frequency Identification (RFID) refers to wireless technology that uses radio waves to automatically identify items within a certain proximity. It is being widely used in various applications, but there is reluctance in the deployment of RFID due to the high cost involved and the challenging problems found in the observed colossal RFID data. The obtained data is of low quality and contains anomalies like false positives, false negatives, and duplication. To enhance the quality of data, cleaning is the essential task, so that the resultant data can be applied for high-end applications. This chapter investigates the existing physical, middleware, and deferred approaches to deal with the anomalies found in the RFID data. A novel hybrid approach is developed to solve data quality issues so that the demand for RFID data will certainly grow to meet the user needs.

Intelligent Agents Framework for RFID Hospitals

2011 ◽  
pp. 316-334 ◽  
Author(s):  
Masoud Mohammadian ◽  
Ric Jentzsch
Keyword(s):  
Data Collection ◽  
Data Acquisition ◽  
Radio Frequency Identification ◽  
Intelligent Agents ◽  
Medical Data ◽  
Time Data ◽  
Raw Data ◽  
Privacy Issue ◽  
Real Time Data ◽  
Frequency Identification

When dealing with human lives, the need to utilize and apply the latest technology to help in saving and maintaining patients’ lives is quite important and requires accurate, near-real-time data acquisition and evaluation. At the same time, the delivery of a patient’s medical data needs to be as fast and as secure as possible. One possible way to achieve this is to use a wireless framework based on radio-frequency identification (RFID). This framework can integrate wireless networks for fast data acquisition and transmission while maintaining the privacy issue. This chapter discusses the development of an agent framework in which RFID can be used for patient data collection. The chapter presents a framework for the knowledge acquisition of patient and doctor profiling in a hospital. The acquisition of profile data is assisted by a profiling agent that is responsible for processing the raw data obtained through RFID and a database of doctors and patients.

scholarly journals A Novel Detection Technique for a Chipless RFID System Using Quantile Regression

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 409 ◽  
Author(s):  
Mohammedhusen Manekiya ◽  
Massimo Donelli ◽  
Abhinav Kumar ◽  
Sreedevi Menon
Keyword(s):  
Quantile Regression ◽  
Radio Frequency Identification ◽  
Proof Of Concept ◽  
Time Data ◽  
Rfid System ◽  
Novel Approach ◽  
Chipless Rfid ◽  
Frequency Identification ◽  
Detection Capabilities ◽  
System Prototype

This work presents a novel approach for improving the detection capabilities of a chipless Radio Frequency Identification (RFID) system based on quantile regression. The main drawback of chipless RFID systems is the limited response of the tags due to the low-quality factor of the resonators, used to encode the information in the tag. The detection becomes very challenging especially for real-time data when noise is present. This work proposes the use of quantile regression to enhance the system performance. A chipless RFID system prototype has been fabricated (as a proof of concept) and experimentally assessed. The obtained results are quite satisfactory in the potentialities of the proposed methodology.

RFID-BASED SYNCHRONIZATION OF INFORMATION FLOW AND MATERIAL FLOW

2008 ◽  
Vol 07 (02) ◽  
pp. 271-274
Author(s):  
HUA-LIN ZHENG ◽  
YUE-PAI WANG ◽  
XI-YUAN WAN
Keyword(s):  
Data Collection ◽  
Radio Frequency ◽  
Information Flow ◽  
Radio Frequency Identification ◽  
Material Flow ◽  
Machining Process ◽  
Collection Method ◽  
Work In Process ◽  
Frequency Identification

RFID (Radio Frequency Identification) technology is put forward as a new data collection method to bridge the gap between information flow and material flow. The data achieved by RFID can be shared by both MES and ERP simultaneously. A simulated WIP (Work In Process) machining process application case study is used in the paper to show how the synchronization is realized.

scholarly journals Pemanfaatan Radio Frequency Identification Mifare RC522 dan Arduino Sebagai Media Validasi Kehadiran Mahasiswa

Infotekmesin ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 50-56
Author(s):  
Andriansyah Zakaria ◽  
Andesita Prihantara
Keyword(s):  
Data Collection ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Human Error ◽  
Rfid Technology ◽  
Student Attendance ◽  
Activity Data ◽  
Student Data ◽  
Frequency Identification ◽  
Student Data Collection

In every academic and student activity, data collection on student meetings is always done. General student data collection activities are still carried out manually by filling in the student attendance form. Besides being able to help and correct problems in lecturing activities, the manual presentation system is not practical in centralized recording and also increases human error in recording. The technology that can be used to add to these shortcomings is Radio Frequency Identification (RFID) in the presence of students. By utilizing RFID technology to approve and MySQL as a database, it is expected that student data collection and recording can be done easily and centrally. It can be concluded from the study that each RFID card used is a unique card identity that functions as a valid marker or identity for students or lecturers in conducting attendance.

Sign in / Sign up

Export Citation Format

Share Document