Radio Frequency Identification (RFID) Data Transmission Security

2021 ◽  
pp. 1613-1620
Author(s):  
Lijie Wang
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Data Transmission ◽  
Rfid Data ◽  
Frequency Identification ◽  
Data Transmission Security

scholarly journals Fast and Reliable Burst Data Transmission for Backscatter Communications

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5418 ◽  
Author(s):  
Jumin Zhao ◽  
Xiaojuan Liu ◽  
Dengao Li
Keyword(s):  
Energy Harvesting ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Data Transmission ◽  
Large Data ◽  
Data Packets ◽  
Frame Length ◽  
Channel Conditions ◽  
Burst Data ◽  
Frequency Identification

Computational radio frequency identification (CRFID) sensors are able to transfer potentially large amounts of data to the reader in the radio frequency range. However, the existing EPC C1G2 protocol is inefficient when there are abundant critical and emergency data to be transmitted and cannot adapt to changing energy-harvesting and channel conditions. In this paper, we propose a fast and reliable method for burst data transmission by fragmenting large data packets into blocks and we introduce a burst transmission mechanism to optimize the EPC C1G2 communication procedure for burst transmission when there are critical and emergency data to be transmitted. In addition, we utilize erasure codes to reduce Acknowledgement (ACK) delay and to improve system reliability. Our results show that our proposed scheme significantly outperforms the current fixed frame length approach and the dynamic frame length and charging time adaptation scheme (DFCA) and that the goodput is close to the theoretically optimal value under different energy-harvesting and channel conditions.

RFIDTango: A Scenario-Based Massive RFID Data Generator

2011 ◽  
Vol 130-134 ◽  
pp. 2086-2089
Author(s):  
Fang Quan Xie ◽  
Zhan Huai Li ◽  
Qun Chen ◽  
Yan Ming Nie ◽  
Shang Lian Peng
Keyword(s):  
Radio Frequency ◽  
Data Management ◽  
Radio Frequency Identification ◽  
Hardware Cost ◽  
Data Generator ◽  
Management Problems ◽  
Rfid Data ◽  
Frequency Identification ◽  
Radio Frequency Identification Technology ◽  
Rfid Data Management

RFID (Radio Frequency IDentification) technology has been widely used in many applications. In recent years, researchers have begun to study various RFID data management problems. Unfortunately, it is difficult for researchers to obtain massive raw RFID data because of hardware cost and limitations of lab environment. We have designed RFIDTango, a massive raw RFID data generator, to simulate real RFID application scenarios. In this paper, we present a system of RFIDTango and show how RFIDTango can simulate a RFID-enabled supermarket scenario effectively and efficiently.

scholarly journals IoT-Based Car's Parking Monitoring System

2018 ◽  
Vol 164 ◽  
pp. 01002
Author(s):  
Albertus Ega Dwiputra ◽  
Handry Khoswanto ◽  
Raymond Sutjiadi ◽  
Resmana Lim
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Data Transmission ◽  
Data Transfer ◽  
Measuring Time ◽  
Accuracy Level ◽  
Parking Lot ◽  
Frequency Identification ◽  
Rate Of Success

Internet-of-things-based technologies have advanced so much and helped public necessities. The use of IoT at a parking lot will help vehicle users to know the availability of a parking location through smartphones. This IoT-based parking system is created by using controllers, sensors, servers and cloud. Controllers and sensors will be placed on the ceiling of each parking slots to detect the presence of a car. Server collect the results of the sensors and store them in Cloud. System test is conducted by installing three sensor circuits and server in a parking lot. The tests consist of measuring time that required for data transmission and the rate of success of data transmission from the parking lot to the Cloud. Based on above tests, it is observed that the sensor circuit and Radio Frequency Identification are able to transmit the parking lot data without error. This system require maximum 1 min to update parking lot data. The process of obtaining data until the data being stored in Cloud takes 12 s and the process of acquiring parking condition data from Cloud to smartphone takes 30 s. The accuracy level of parking lot data transfer is 100 %.

Design of Laboratory Management System Based on RFID

2014 ◽  
Vol 945-949 ◽  
pp. 2689-2692 ◽  
Author(s):  
Shu Qing Ma ◽  
Chuan Jun Wang
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Data Transmission ◽  
Data Exchange ◽  
Automatic Identification ◽  
Rfid Technology ◽  
Laboratory Management ◽  
Ic Card ◽  
Frequency Identification ◽  
Control Management

RFID (Radio Frequency Identification, RFID) technology is developed in the eighty s of the 20th century a automatic Identification technology. Using radio frequency way between non-contact rf card reader and two-way data transmission, in order to achieve the purpose of target recognition and data exchange. Article from the traditional type of code, compared magnetic card and IC card, rf card has a non-contact, fast reading, no wear, is not affected by the environment, the characteristics of long service life, easy to use and have anti-collision function, can handle multiple CARDS at the same time. Abroad, rfid technology has been widely used in industrial automation, business automation, transportation control management, and many other fields.

CEP-Based Massive Data Processing Approach for RFID Data

2011 ◽  
Vol 317-319 ◽  
pp. 350-353 ◽  
Author(s):  
Chang Hong Liu ◽  
Run Yang Zhong ◽  
Yi Er Yan ◽  
Xiao Hu
Keyword(s):  
Data Processing ◽  
Radio Frequency ◽  
Data Management ◽  
Radio Frequency Identification ◽  
Model Solution ◽  
Massive Data ◽  
Data Process ◽  
Rfid Data ◽  
Frequency Identification ◽  
Massive Data Processing

Complex Event Processing (CEP) is proposed in this paper to tackle the changeability, tense correlation, and association in massive data process. This paper takes RFID (Radio Frequency Identification) data for example to illustrate how CEP works on dealing with massive data processing. First, semantic expressions are introduced as the reason of modeling for CEP. Then, model solution based on semantic expressions is proposed. Finally, this methodology achieves good results in processing massive RFID data in terms of speed, efficiency and veracity. The experiment results demonstrate that it is better in getting rid of complexity data after comparing with traditional data management based on database with massive data.

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