scholarly journals BEI-TAB: Enabling Secure and Distributed Airport Baggage Tracking with Hybrid Blockchain-Edge System

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Pengbo Si ◽  
Fei Wang ◽  
Enchang Sun ◽  
Yuzhao Su
Keyword(s):  
Real Time ◽  
Radio Frequency Identification ◽  
Information Leakage ◽  
Byzantine Fault Tolerance ◽  
Consensus Protocol ◽  
Credit Score ◽  
Consistency Protocol ◽  
Low Efficiency ◽  
Ciphertext Policy ◽  
Business Requirements

Global air transport carries about 4.3 billion pieces of baggage each year, and up to 56 percent of travellers prefer obtaining real-time baggage tracking information throughout their trip. However, the traditional baggage tracking scheme is generally based on optical scanning and centralized storage systems, which suffers from low efficiency and information leakage. In this paper, a blockchain and edge computing-based Internet of Things (IoT) system for tracking of airport baggage (BEI-TAB) is proposed. Through the combination of radio frequency identification technology (RFID) and blockchain, real-time baggage processing information is automatically stored in blockchain. In addition, we deploy Interplanetary File System (IPFS) at edge nodes with ciphertext policy attribute-based encryption (CP-ABE) to store basic baggage information. Only hash values returned by the IPFS network are kept in blockchain, enhancing the scalability of the system. Furthermore, a multichannel scheme is designed to realize the physical isolation of data and to rapidly process multiple types of data and business requirements in parallel. To the best of our knowledge, it is the first architecture that integrates RFID, IPFS, and CP-ABE with blockchain technologies to facilitate secure, decentralized, and real-time characteristics for storing and sharing data for baggage tracking. We have deployed a testbed with both software and hardware to evaluate the proposed system, considering the performances of transaction processing time and speed. In addition, based on the characteristics of consortium blockchain, we improved the practical Byzantine fault tolerance (PBFT) consensus protocol, which introduced the node credit score mechanism and cooperated with the simplified consistency protocol. Experimental results show that the credit score-based PBFT consensus (CSPBFT) can shorten transaction delay and improve the long-term running efficiency of the system.

scholarly journals False Positive RFID Detection Using Classification Models

2019 ◽  
Vol 9 (6) ◽  
pp. 1154 ◽  
Author(s):  
Ganjar Alfian ◽  
Muhammad Syafrudin ◽  
Bohan Yoon ◽  
Jongtae Rhee
Keyword(s):  
Machine Learning ◽  
Supply Chain ◽  
Real Time ◽  
Outlier Detection ◽  
Radio Frequency Identification ◽  
False Positives ◽  
Machine Learning Algorithms ◽  
Classification Model ◽  
Automated Identification ◽  
Rfid Data

Radio frequency identification (RFID) is an automated identification technology that can be utilized to monitor product movements within a supply chain in real-time. However, one problem that occurs during RFID data capturing is false positives (i.e., tags that are accidentally detected by the reader but not of interest to the business process). This paper investigates using machine learning algorithms to filter false positives. Raw RFID data were collected based on various tagged product movements, and statistical features were extracted from the received signal strength derived from the raw RFID data. Abnormal RFID data or outliers may arise in real cases. Therefore, we utilized outlier detection models to remove outlier data. The experiment results showed that machine learning-based models successfully classified RFID readings with high accuracy, and integrating outlier detection with machine learning models improved classification accuracy. We demonstrated the proposed classification model could be applied to real-time monitoring, ensuring false positives were filtered and hence not stored in the database. The proposed model is expected to improve warehouse management systems by monitoring delivered products to other supply chain partners.

An Intelligent and Secure Framework for Wireless Information Technology in Healthcare for User and Data Classification in Hospitals

2019 ◽  
pp. 248-276
Author(s):  
Masoud Mohammadian ◽  
Dimitrios Hatzinakos ◽  
Petros Spachos ◽  
Ric Jentzsh
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Radio Frequency Identification ◽  
Data Classification ◽  
Patient Data ◽  
Hospital Environment ◽  
Time Data ◽  
Privacy And Security ◽  
Real Time Data ◽  
Frequency Identification

Real time data acquisition and evaluation are required to save lives. Such data with utilization and application of the latest technologies in hospitals around the world can improve patient treatments and well beings. The delivery of patient's medical data needs to be secure. Secure and accurate real time data acquisition and analysis of patient data and the ability to update such data will assist in reducing cost while improving patient's care. A wireless framework based on radio frequency identification (RFID) can integrate wireless networks for fast data acquisition and transmission, while maintaining the privacy issue. This chapter discusses the development of a framework that can be considered for secure patient data collection and communications in a hospital environment. A new method for data classification and access authorization has also been developed, which will assist in preserving privacy and security of data. Several Case studies are offered to show the effectiveness of this framework.

An Intelligent and Secure Framework for Wireless Information Technology in Healthcare for User and Data Classification in Hospitals

2016 ◽  
pp. 452-479
Author(s):  
Masoud Mohammadian ◽  
Dimitrios Hatzinakos ◽  
Petros Spachos ◽  
Ric Jentzsh
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Radio Frequency Identification ◽  
Data Classification ◽  
Patient Data ◽  
Hospital Environment ◽  
Time Data ◽  
Privacy And Security ◽  
Real Time Data ◽  
Frequency Identification

Real time data acquisition and evaluation are required to save lives. Such data with utilization and application of the latest technologies in hospitals around the world can improve patient treatments and well beings. The delivery of patient's medical data needs to be secure. Secure and accurate real time data acquisition and analysis of patient data and the ability to update such data will assist in reducing cost while improving patient's care. A wireless framework based on radio frequency identification (RFID) can integrate wireless networks for fast data acquisition and transmission, while maintaining the privacy issue. This chapter discusses the development of a framework that can be considered for secure patient data collection and communications in a hospital environment. A new method for data classification and access authorization has also been developed, which will assist in preserving privacy and security of data. Several Case studies are offered to show the effectiveness of this framework.

Reducing Tracking Error in RFID Real-Time Localization Systems Using Kalman Filters

2014 ◽  
Vol 5 (3) ◽  
pp. 1-24
Author(s):  
Benjamin Sanda ◽  
Ikhlas Abdel-Qader ◽  
Abiola Akanmu
Keyword(s):  
Real Time ◽  
Radio Frequency Identification ◽  
Kalman Filters ◽  
Tracking Error ◽  
Time Of Arrival ◽  
Indoor Environments ◽  
Real World Data ◽  
Localization Accuracy ◽  
Accurate Localization ◽  
Localization Systems

The use of Radio Frequency Identification (RFID) has become widespread in industry as a means to quickly and wirelessly identify and track packages and equipment. Now there is a commercial interest in using RFID to provide real-time localization. Efforts to use RFID technology in this way experience localization errors due to noise and multipath effects inherent to these environments. This paper presents the use of both linear Kalman filters and non-linear Unscented Kalman filters to reduce the error rate inherent to real-time RFID localization systems and provide more accurate localization results in indoor environments. A commercial RFID localization system designed for use by the construction industry is used in this work, and a filtering model based on 3rd order motion is developed. The filtering model is tested with real-world data and shown to provide an increase in localization accuracy when applied to both raw time of arrival measurements as well as final localization results.

scholarly journals A New Online Dynamic Testing Method for Noise of Broadcast Transmitter

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shan-Shan Li ◽  
Jian Zhou ◽  
Xuan Wang
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Dynamic Testing ◽  
Noise Figure ◽  
Estimation Algorithm ◽  
Test Method ◽  
Noise Estimation ◽  
Experimental Simulation ◽  
Spectrum Estimation ◽  
Low Efficiency

Aiming at the shortcomings of traditional broadcast transmitter noise test methods, such as low efficiency, inconvenient data storage, and high requirements for testers, a dynamic online test method for transmitter noise is proposed. The principle of system composition and test method is given. The transmitter noise is real-time changing. The Voice Active Detection (VAD) noise estimation algorithm cannot track the transmitter noise change in real time. This paper proposes a combined noise estimation algorithm for VAD and dynamic estimation. By setting the threshold of the double-threshold VAD detection to be low, it can accurately detect the silent segment. The silent segment is used as a noise signal for noise estimation. For the nonsilent segment detected by the VAD, a minimum value search dynamic spectrum estimation algorithm based on the existence probability of the speech (IMCRA) is used for noise estimation. Transmitter noise is measured by calculating the noise figure (NF).The test method collects the input and output data of the transmitter in real time, which has better accuracy and real-time performance, and the feasibility of the method is verified by experimental simulation.

Cassandra-based data repository design for food supply chain traceability

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sandeep Kumar Singh ◽  
Mamata Jenamani
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Radio Frequency Identification ◽  
Query Language ◽  
Data Repository ◽  
Time Data ◽  
Content Type ◽  
The Real ◽  
Traceability System ◽  
Real Time Data

Purpose The purpose of this paper is to design a supply chain database schema for Cassandra to store real-time data generated by Radio Frequency IDentification technology in a traceability system. Design/methodology/approach The real-time data generated in such traceability systems are of high frequency and volume, making it difficult to handle by traditional relational database technologies. To overcome this difficulty, a NoSQL database repository based on Casandra is proposed. The efficacy of the proposed schema is compared with two such databases, document-based MongoDB and column family-based Cassandra, which are suitable for storing traceability data. Findings The proposed Cassandra-based data repository outperforms the traditional Structured Query Language-based and MongoDB system from the literature in terms of concurrent reading, and works at par with respect to writing and updating of tracing queries. Originality/value The proposed schema is able to store the real-time data generated in a supply chain with low latency. To test the performance of the Cassandra-based data repository, a test-bed is designed in the lab and supply chain operations of Indian Public Distribution System are simulated to generate data.

scholarly journals An Implantable Inductive Near-Field Communication System with 64 Channels for Acquisition of Gastrointestinal Bioelectrical Activity

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2810 ◽  
Author(s):  
Amir Javan-Khoshkholgh ◽  
Aydin Farajidavar
Keyword(s):  
Real Time ◽  
Radio Frequency Identification ◽  
Communication System ◽  
Near Field ◽  
Data Communication ◽  
Near Field Communication ◽  
Bioelectrical Activity ◽  
Real Time Monitoring ◽  
Rf Transceiver

High-resolution (HR) mapping of the gastrointestinal (GI) bioelectrical activity is an emerging method to define the GI dysrhythmias such as gastroparesis and functional dyspepsia. Currently, there is no solution available to conduct HR mapping in long-term studies. We have developed an implantable 64-channel closed-loop near-field communication system for real-time monitoring of gastric electrical activity. The system is composed of an implantable unit (IU), a wearable unit (WU), and a stationary unit (SU) connected to a computer. Simultaneous data telemetry and power transfer between the IU and WU is carried out through a radio-frequency identification (RFID) link operating at 13.56 MHz. Data at the IU are encoded according to a self-clocking differential pulse position algorithm, and load shift keying modulated with only 6.25% duty cycle to be back scattered to the WU over the inductive path. The retrieved data at the WU are then either transmitted to the SU for real-time monitoring through an ISM-band RF transceiver or stored locally on a micro SD memory card. The measurement results demonstrated successful data communication at the rate of 125 kb/s when the distance between the IU and WU is less than 5 cm. The signals recorded in vitro at IU and received by SU were verified by a graphical user interface.

Remote Monitoring System of the Rivers and Lakes' Water Quality Based on GPRS and 3G Technology

2014 ◽  
Vol 898 ◽  
pp. 618-623
Author(s):  
Meng Xia An ◽  
Ji Ping Xu ◽  
Xiao Yi Wang ◽  
Jia Bin Yu ◽  
Hui Yan Zhang ◽  
...  
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Data Communication ◽  
Water Quality Monitoring ◽  
Management Decision ◽  
Remote Monitoring System ◽  
Rivers And Lakes ◽  
Low Efficiency

In view of the methods on remote monitoring of the rivers and lakes water quality are relatively single and low efficiency in supervision at present, this page puts forward a kind of design method of the internet of things system about remote monitoring system based on GPRS/3G technology. The system can realize multi-point data integration, processing, integration and real-time results releasing, with GPRS/3G remote data communication technology as the core, and send the information accesses to the buoys placed on the waters surface, mobile intelligent instruments, and the water quality monitoring ark placed on the water bank via GPRS/3G module to the superior intelligence analysis system, which realizes the real-time display in the GIS map, water quality evaluation, bloom forecast, decision-making, etc. Practice has proved that this system is stable and reliable, and provided the effective monitoring of the rivers and lakes water quality and management decision of algae blooms emergency for the environmental protection department.

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