Radio Frequency Identification Sensor Research Articles

Use of Chipless Radio Frequency Identification Technology for Smart Food Packaging: An Economic Analysis for an Australian Seafood Industry

Effective monitoring of perishable food products has become increasingly important for ensuring quality, enabling smart packaging to be a key consideration for food companies. Among the promising technologies available for transforming packaging into intelligent packaging, chipless radio frequency identification (RFID) sensors stand out. Despite the high initial implementation costs associated with chipless RFID technology, the potential benefits could outweigh the costs if electrical challenges can be overcome. We examine various economic methods to analyze the economic benefits of chipless RFID technology, evaluating the benefits of using this technology for the quality monitoring of seafood products of an Australian seafood producer, Tassal. The analysis considers three primary business drivers, viz. quality monitoring, operational efficiency, and tracking and tracing, using net present value and return on investment as the key indicators to assess the feasibility of implementing the technology. Based on sensitivity analysis, we suggest chipless RFID technology is currently best suited for large firms facing significant quality monitoring and operational efficiency challenges. However, as the cost of chipless RFID sensors decreases with further development, this technology may become a more viable option for small businesses in the future.

CoDuBoTeSS: A Pilot Study to Eradicate Counterfeit Drugs via a Blockchain Tracer Support System on the Nigerian Frontier

The pharma-sector has maintained improved productivity and profitability via a concerted effort to address critical issues such as an unorganized regulatory system, lack of safety data, no standards in manufacture process, non-adaptation to pharma-chain, and no-harmony of inventory supports. Study proposes blockchain trace-support to ensure drugs quality, consumer safety, and its trading as asset. It uses a radio-frequency identification sensor to register manufacture and administration process, and provide a databank to trace drug records. Results notes: (a) presents a roadmap for adoption by the National Agency for Food and Drug Administration and Control (NAFDAC) to ensure a traceable pharmaceutical blockchain, (b) show ensemble is scalable for up-to 7500users to yield a performance of 1138-transactions per seconds with response time of 88secs for page retrieval and 128secs for queries respectively, and (c) yields slightly longer time for increased number of users via its world-state as stored in the permissionless blockchain hyper-fabric ledger. Thus, the framework can directly query and retrieve data without it traversing the whole ledger. This, in turn, improves the efficiency and effectiveness of the traceability system. Keywords: Blockchain, Counterfeit drugs, Healthcare, Nigeria, CORDA, hyper-ledger fabric, HIPPA Journal Reference Format: Ifioko, A.M., Yoro, R.E., Okpor, M.D., Brizimor, S.E, Obasuyi, D., Emordi, F.U., Odiakaose, C.C., Ojugo, A.A., Atuduhor, R.R, Abere, R.A., Ejeh, P.O., Ako, R.E. & Geteloma, V.O. (2024): CoDuBoTeSS: A Pilot Study to Eradicate Counterfeit Drugs via a Blockchain Tracer Support System on the Nigerian Frontier. Journal of Behavioural Informatics, Digital Humanities and Development Rese Vol. 10 No. 2. Pp 53-74 https://www.isteams.net/behavioralinformaticsjournal dx.doi.org/10.22624/AIMS/BHI/V10N2P6

CoDuBoTeSS: A Pilot Study to Eradicate Counterfeit Drugs via a Blockchain Tracer Support System on the Nigerian Frontier

The pharma-sector has maintained improved productivity and profitability via a concerted effort to address critical issues such as an unorganized regulatory system, lack of safety data, no standards in manufacture process, non-adaptation to pharma-chain, and no-harmony of inventory supports. Study proposes blockchain trace-support to ensure drugs quality, consumer safety, and its trading as asset. It uses a radio-frequency identification sensor to register manufacture and administration process, and provide a databank to trace drug records. Results notes: (a) presents a roadmap for adoption by the National Agency for Food and Drug Administration and Control (NAFDAC) to ensure a traceable pharmaceutical blockchain, (b) show ensemble is scalable for up-to 7500users to yield a performance of 1138-transactions per seconds with response time of 88secs for page retrieval and 128secs for queries respectively, and (c) yields slightly longer time for increased number of users via its world-state as stored in the permissionless blockchain hyper-fabric ledger. Thus, the framework can directly query and retrieve data without it traversing the whole ledger. This, in turn, improves the efficiency and effectiveness of the traceability system. Keywords: Blockchain, Counterfeit drugs, Healthcare, Nigeria, CORDA, hyper-ledger fabric, HIPPA Journal Reference Format: Ifioko, A.M., Yoro, R.E., Okpor, M.D., Brizimor, S.E, Obasuyi, D., Emordi, F.U., Odiakaose, C.C., Ojugo, A.A., Atuduhor, R.R, Abere, R.A., Ejeh, P.O., Ako, R.E. & Geteloma, V.O. (2024): CoDuBoTeSS: A Pilot Study to Eradicate Counterfeit Drugs via a Blockchain Tracer Support System on the Nigerian Frontier. Journal of Behavioural Informatics, Digital Humanities and Development Rese Vol. 10 No. 2. Pp 53-74 https://www.isteams.net/behavioralinformaticsjournal dx.doi.org/10.22624/AIMS/BIJ/V10N1P6

An asynchronous wireless network for capturing event-driven data from large populations of autonomous sensors

Networks of spatially distributed radiofrequency identification sensors could be used to collect data in wearable or implantable biomedical applications. However, the development of scalable networks remains challenging. Here we report a wireless radiofrequency network approach that can capture sparse event-driven data from large populations of spatially distributed autonomous microsensors. We use a spectrally efficient, low-error-rate asynchronous networking concept based on a code-division multiple-access method. We experimentally demonstrate the network performance of several dozen submillimetre-sized silicon microchips and complement this with large-scale in silico simulations. To test the notion that spike-based wireless communication can be matched with downstream sensor population analysis by neuromorphic computing techniques, we use a spiking neural network machine learning model to decode prerecorded open source data from eight thousand spiking neurons in the primate cortex for accurate prediction of hand movement in a cursor control task.

Biosensors and its diverse applications in healthcare systems

Abstract This paper provides a thorough analysis of recent developments in radio frequency identification (RFID)-based biosensors and their uses in the medical industry. The most recent and cutting-edge technologies used in RFID sensors, as well as their operational procedures in the medical industry, are the main focus of this article. The most effective design methodology for RFID biosensors is determined by evaluating various design methodologies. The present state of the art technologies in this domain are also analyzed and discussed. This paper aims to support researchers in the development of inexpensive and widely available RFID-based biosensors that can improve medical and healthcare outcomes. The use of RFID biosensors in contemporary medical applications has demonstrated significant promise for enhancing patient care and facilitating the early diagnosis of a number of diseases. It is anticipated that RFID biosensor technology will maintain to play a significant role in the development of the medical field as it undergoes further development.

Displacement Estimation via 3D-Printed RFID Sensors for Structural Health Monitoring: Leveraging Machine Learning and Photoluminescence to Overcome Data Gaps.

Monitoring object displacement is critical for structural health monitoring (SHM). Radio frequency identification (RFID) sensors can be used for this purpose. Using more sensors enhances displacement estimation accuracy, especially when it is realized through the use of machine learning (ML) algorithms for predicting the direction of arrival of the associated signals. Our research shows that ML algorithms, in conjunction with adequate RFID passive sensor data, can precisely evaluate azimuth angles. However, increasing the number of sensors can lead to gaps in the data, which typical numerical methods such as interpolation and imputation may not fully resolve. To overcome this challenge, we propose enhancing the sensitivity of 3D-printed passive RFID sensor arrays using a novel photoluminescence-based RF signal enhancement technique. This can boost received RF signal levels by 2 dB to 8 dB, depending on the propagation mode (near-field or far-field). Hence, it effectively mitigates the issue of missing data without necessitating changes in transmit power levels or the number of sensors. This approach, which enables remote shaping of radiation patterns via light, can herald new prospects in the development of smart antennas for various applications apart from SHM, such as biomedicine and aerospace.

Digitally-defined ultrathin transparent wireless sensor network for room-scale imperceptible ambient intelligence

Wireless and battery-free radio-frequency (RF) sensors can be used to create physical spaces that ambiently sense and respond to human activities. Making such sensors ultra-flexible and transparent is important to preserve the aesthetics of living environments, accommodate daily activities, and functionally integrate with objects. However, existing RF sensors are unable to simultaneously achieve high transparency, flexibility, and the electrical conductivity required for remote room-scale operation. Here, we report 4.5 µm RF tag sensors achieving transparency exceeding 90% that provide capabilities in room-scale ambient wireless sensing. We develop a laser-assisted water-based adhesion-reversion process to digitally realize computer-aided RF design at scale. By individually tagging multiple objects and regions of the human body, we demonstrate multiplexed wireless tracking of human-environment interactions and physiological signals at a range of up to 8 m. These radio-frequency identification sensors open opportunities for non-intrusive wireless sensing of daily living spaces for applications in health monitoring and elderly care.

Magnetic Permeability Perturbation-Based RFID Sensor for Pipeline Internal Corrosion Monitoring

Radio frequency identification (RFID) sensors for pipeline corrosion monitoring have been considered an attractive area due to the advantages of battery-free and maintenance-free. Due to the skin effect of high-frequency electromagnetic waves, existing RFID sensors can only detect the surface corrosion of pipelines. To realize internal corrosion monitoring, a magnetic permeability perturbation-based RFID sensing method was developed in this paper. Under direct-current (DC) magnetization, internal corrosion causes magnetic field distortions and incurs magnetic permeability perturbations in the skin layer of surface. These perturbations can be detected by the RFID sensor. Considering the resonance frequency shift (RFS) as a feature, a patch antenna sensitive to magnetic permeability was designed. Moreover, steel plates with artificial internal defects were simulated and tested to validate the feasibility of the proposed method. It was observed that the surface magnetic permeability perturbations caused by internal corrosions of different depths incur different RFS values. Finally, pipelines with artificial and natural internal corrosions were tested to validate the feasibility of the proposed method. The RFS caused by the natural corrosion was 4.26 MHz, and the RFS caused by the sound area was 1.63 MHz. The proposed magnetic permeability perturbation-based RFID method provides a promising method for pipeline internal corrosion monitoring with the application of RFID sensing technology.

Design Smart Classroom Based IoT at SMP Ali Bin Abi Tholib

A classroom is a room that functions as a place for teaching and learning activities. In the classroom there are also various tools to support teaching and learning activities such as tables, whiteboards and other electronic equipment. The importance of using technology in teaching and learning classrooms is because current needs are increasing with the times.Smart Classroom is a technology that makes the class have an automation system with very sophisticated performance. This system utilizes technology that can control electronic equipment in the classroom automatically. The high level of negligence of electronic device users in turning off electronic items that are often on continuously, such as lights, air conditioners, projectors, results in wastage of electrical energy. To overcome this problem, researchers built an automation system in classrooms using the IoT system. The research method used is an experimental model. This automatic system is programmed by the Arduino application by creating a security system using Radio Frequency Identification (RFID) as the radio frequency data carrier that will be received by the receiver. The results of this research are a smart classroom prototype using RFID that can operate well. The RFID sensor's ability to detect the ID between the Card and Reader is a maximum distance of 1cm. The Reader's ability to detect ID cards takes 2 to 3 seconds from when the ID card is attached to the Reader and this tool will work when the user attaches the RFID to the reader so that all connected equipment will automatically turn ON such as lights, AC and projectors.

Counterfeit Drugs Detection in the Nigeria Pharma-Chain via Enhanced Blockchain-based Mobile Authentication Service

Drugs has since become a major source of livelihood for Nigerians. It also accounts for over 85% of the total food consumed within her borders. The sector has maintained improved productivity and profitability via a concerted effort to address critical issues such as an unorganized regulatory system, lack of food safety data, no standards in agricultural produce, non-adaptation to precision farming, and non-harmony via inventory trace supports. This study proposes blockchain-based tracer-support system in a continued effort to ensure food quality, consumer safety, and trading of food assets. It uses the radio-frequency identification sensors to register and trace drugs manufacture cum administration process and provide a databank to trace the drug records via the shipment to its distribution centers. To ascertain, if the drug is genuine or fake, the user scans the QRcode via the mobile application API, which then generates feedback. Results achieves the following: (a) presents a framework and roadmap for adoption by the National Agency for Food and Drug Administration and Control (NAFDAC) to ensure pharmaceutical blockchain, (b) show ensemble is scalable for up-to 7500users to yield a performance of 1138-transactions per seconds with response time of 88secs for page retrieval and 128secs for queries respectively, and (c) yields slightly longer time for increased number of users via its world-state as stored in the permissionless blockchain hyper-fabric ledger. Thus, the framework can directly query and retrieve data without it traversing the whole ledger. This, in turn, improves the efficiency and effectiveness of the traceability system. Keywords: Nigerian Pharma-Chain, Fake/Counterfeit drugs, Healthcare, CORDA, hyper-ledger fabric, NAFDAC Ejeh, P.O., Okpor, M.D., Yoro, R.E., Ifioko, A.M., Onyemenem, I.S., Odiakaose, C,C., Ojugo, A.A., Ako, R.E., Emordi, F.U., Geteloma, V.O., Counterfeit Drugs Detection in the Nigeria Pharma-Chain via Enhanced Blockchain-based Mobile Authentication Service. Journal of Advances in Mathematical & Computational Science. 2024, Vol. 12, No. 1. Pp 25-44. Available online at www.isteams.net/mathematics-computationaljournal. dx.doi.org/10.22624/AIMS/MATHS/V12N2P3

Challenges for Embedding RFID Sensors in Reinforced Concrete for Low‐effort Structural Health Monitoring

AbstractThe structural health of civil infrastructure can be monitored using non‐destructive testing methods and wireless sensor technology. Buildings are often made of reinforced concrete, in which the sensors can be embedded during construction. The implementation of sensor‐based monitoring therefore fundamentally requires robust electronics. The wireless sensors must meet the special requirements of different areas such as communication, durability in the concrete, and compatibility with future readers. Taking into account previous approaches from practice and research, an elicitation of basic requirements for a Radio Frequency Identification (RFID) sensor system that can be embedded in concrete was carried out. Specific problems related to embedding electronic sensors in concrete and their design are investigated. Simple RFID sensor systems have been developed that allow operation without cables or batteries. The main sensor requirements are listed accordingly. Challenges and issues that need to be considered when using RFID sensors in concrete are described. Finally, the “life cycle” of a sensor system embedded in reinforced concrete is briefly discussed.

Improved distribution and food safety for beef processing and management using a blockchain-tracer support framework

<span lang="EN-US">Agriculture has since become a major source of livelihood for Nigerians. It also accounts for over 85% of the total food consumed within her borders. The sector has maintained improved productivity and profitability via a concerted effort to address critical issues such as an unorganized regulatory system, lack of food safety data, no standards in agricultural produce, non-adaptation to precision farming, and non-harmony via inventory trace supports. This study proposes blockchain-based trace-support in a continued effort to ensure food quality, consumer safety, and trading of food assets. It uses the radio frequency identification (RFID) sensor to register and track livestocks, farms/farmers, and abattoir processes as well as provisions a databank to trace livestock data. Results show the model adequately perform about 1,101 transactions per seconds with a response time of 0.21 s for queries and 0.28 s for https pages respectively for 2,500 users. Also, it yields a slightly longer time of 0.32 s for queries and 0.38 s for https pages respectively with an increased 5,000 users via the world-state as stored in the blockchain’s hyper-fabric ledger. Overall, the framework can directly query and retrieve data without it traversing the whole ledger. This, in turn, improves the efficiency and effectiveness of the traceability system.</span>

IOT Pada Purwarupa Sistem Keamanan Pintu Kantor Dengan Sensor RFID dan PIR Berbasis Telegram

The proposed office door security system combines RFID (Radio-Frequency Identification) Sensor and PIR (Passive Infrared) Sensor technology with Telegram-based communication. The design of this system requires RFID and PIR sensors to be formed in order to produce a system design that is made to meet the needs of system users. The aim of this system is to increase the security level of access to office space by combining identification of access owners via RFID cards and motion detection using PIR sensors. Communication through the Telegram platform is used to provide real-time notifications to access owners when there is activity at the office door. The control system for this device is controlled by the Esp32 Microcontroller, using 4 inputs, namely Rfid, PIR, Keypad and telegram sensors, as well as 5 outputs, namely Selenid Doorlock, Buzzer, LCD, Relay and telegram. By using the esp32 microcontroller to process data and the telegram application for IoT as a link between devices and smartphones. With 2 sensors as logic inputs for the esp32 microcontroller, the number of outputs that occur is 5, namely in the form of a sound from a buzzer as a warning, and a PIR as a sensor to open the door from the inside. When opening the RFID with a card tag, then the selenoid doorlock will open. Overall, the design of this office door security system has the potential to improve security and monitoring in the office space. By combining the technology of RFID sensors, PIR sensors and Telegram-based communication, this system enables accurate identification, real-time motion detection and fast interaction between the security system and the access owner. So that Telegram is successful in sending notifications if someone enters, that is, they will appear. "User Name Open Door: according to the registered UID", but if it fails "Unregistered User Failed Login Attempt" The LCD will also issue an output if someone has registered their RFID tag or not

Design of Domino-Resonators for Enhanced Power and Data Transmission of 13.56 MHz RFID Sensors

This paper presents a straightforward design algorithm to enhance power and data transmission for 13.56 MHz Radio Frequency Identification (RFID) sensor applications by using domino-resonators. In this algorithm, the transformed transponder impedance and modulation depth seen at the reader antenna are formulated and modeled under the presence of domino-resonators. To improve the accuracy, voltage-clamped mode of the tag Integrated Circuit (IC) is considered, which enables accurate calculation of the maximum readable distance, transferred power and equivalent tag IC impedance. For the sake of simplicity, a type-A ultralight tag IC is used and modeled, while all resonators and tag antenna dimensions are based on standard smart-card sized coils. The design algorithm is coded in MATLAB for a 5-coil RFID system, i.e. with three identical domino-resonators, and verified using LT-Spice simulations. For experimental validation, the designed 5-coil RFID system is implemented for enhancing the distance between a commercial 13.56 MHz RFID reader and ISO/IEC 14443A standard RFID tag IC.

A multiple fault diagnosis approach for transformer based on double antenna RFID sensor and PSA-optimized LSTM

This work aims to realize multiple mechanical fault diagnosis for transformers in the incubation period. A double antenna radio frequency identification (RFID) sensor is used to obtain vibration signals generated by a transformer. The measured raw vibration signals have prominent nonlinear characteristics; besides, they are mixed with vast noises, such as electromagnetic interference, measurement disturbance and so on, making it challenging to identify distinguishable features from the measured data. The long short-term memory (LSTM), which exhibits satisfactory performance in dealing with large-scale nonlinear time-series signals, is adopted to extract features from high-dimensional raw signals. Because the parameters of the LSTM cell and support vector machine significantly determine the accuracy of diagnosis, these parameters are determined using the chaotic quantum particle swarm optimization algorithm. Moreover, the sparse periodical attention (PSA) mechanism is used to enhance the LSTM model’s performance by focusing on global feature learning and determining the input data length. The experimental results verify that the exploited RFID sensor realizes reliable data wireless transmission within 17.5 m. Moreover, the PSA-optimized LSTM approach achieves satisfactory trade-off between diagnosis accuracy and computation complexity while dealing with multiple mechanical fault diagnosis of a transformer in early stages.

A Compact Low-Loss Reflection-Type Harmonic Transponder for Battery-Less RFID Sensors Based on Harmonic Backscattering

This study presents a compact reflection-type harmonic transponder with a wide input power range for battery-less radio frequency identification (RFID) sensors based on harmonic backscattering. Miniaturizing the circuit size of conventional harmonic transponders is difficult because the input and output matching stages are configured separately, and two antennas are used for each port. The proposed harmonic transponder based on a dual-band matching network matches the load simultaneously at the fundamental and second harmonic frequencies over a wide input power range, thus enhancing the conversion gain (CG) with a compact size. For verification, the proposed transponder is implemented in a compact size with dimensions of 19 mm × 17.8 mm. The measured CG of the implemented transponder is maintained at over −10 dB in the wide input power range of −6.4 dBm to 10.6 dBm at 2.45 GHz. Th e harmonic transponder is configured with a dual-band chip antenna and measured in free space to verify whether it is suitable for battery-less RFID sensors. The measured detectable effective distance to the proposed circuit is 6.3 m in free space, with an equivalent isotropically radiated power of 42.6 dBm.

From Chip-Based to Chipless RFID Sensors: A Review

Radio Frequency Identification (RFID) sensors have received increasing attention in recent years due their wireless battery-free operation, low-profile, simplicity, low-cost, and multimodality sensitivity. They have found their way to everyday applications including smart packaging for food quality assurance, early noxious gas detection, smart bandages for chronic wound assessment, and structural health monitoring. This work aims to provide a review of chip-based and chipless RFID sensor technology and to depict a transition from the former to the later one. This is conducted by highlighting existing challenges for implementation of chipless RFIDs, possible solutions to overcome these problems, and recent development introduced in the literature. Then, it has been demonstrated how RFID sensors in conjunction with artificial intelligence and machine learning can be applied for enhancing RFID tag sensitivity and selectivity to a high degree of accuracy. The focus of this paper is on chipless RFID sensors, and at the end the authors present a direction for future research work.

Performance evaluation of a UHF passive RFID tag embedded in a carbon fibre-reinforced polymer

Data collection during the production process plays a key role in the management and control of goods within the company. In this work, the main focus is on the possibility of embedding radio frequency identification (RFID) technology in carbon-fibre reinforced polymer (CFRP) components to evaluate the readability of commercial Ultra High Frequency system by varying their covers, which is also partly in CFRPS. The samples produced and the tags used derived on previous studies, in which configurations with the tag housed inside were established and studied. Two RFID tags were studied that could withstand the harsh environmental conditions, i.e., high temperatures and pressure. This work was not carried out in an ideal environment to assess the theoretical capabilities of RFID sensors, but to understand and evaluate the readability limits of commercial RFID tags embedded in CFRPs. Therefore, an experimental campaign was undertaken to assess the downstream readability of the curing process of tags in laminated mock-ups. It was observed that the curing process had minimal effect on the readability of the tags. Free-space tests were carried out in proximity of metallic elements to determine the change of the reading distance obtained during the test, keeping the fixed antenna used constant.

Chipless RFID Sensors for IoT Sensing and Potential Applications in Underground Mining—A Review

Chipless radio frequency identification (RFID) sensors have enormous potential for underground mining applications since this technology has the potential to meet all the requirements, such as wireless communication, maintenance-free, long lifespan, and battery-free, required to deploy in harsh underground environments. This paper has analysed existing frequency domain chipless RFID sensor technologies to understand suitability for potential applications, such as environmental condition monitoring, support system stability detection, and health monitoring of mining structures in underground mining sites. In light of the analysis, the paper has presented a new classification based on sensing materials and intrinsic sensing parameters such as effective length, coupling, conductivity and permittivity. Furthermore, the analysis has considered accuracy, performance and readability using 3D Electromagnetic (EM) analysis software, CST Studio Suite. Finally, based on our critical analysis and experimental simulations, the paper has identified challenges that need to be addressed by future research for chipless RFID sensors in the underground mining application domain.

Performance Evaluation of a Dynamic Signal Control System for Mixed Traffic Conditions Using Sparse Data

Dynamic signal control systems combine traditional traffic signals with an array of sensors to intelligently control vehicle and pedestrian traffic. Under mixed traffic conditions similar to that prevailing in India, where there are a variety of vehicle classes moving without lane discipline, implementation of such dynamic signal control systems is challenging. This is because automated sensors such as loop detectors used for data collection under homogeneous traffic conditions do not work well under mixed traffic conditions. Under such conditions, the possibility of utilizing sparse data obtained with respect to sampled travel times from different sensors is currently being explored. The present study focuses on developing a dynamic signal control system using sparse data collected using radio frequency identification (RFID) sensors under mixed traffic conditions. An existing delay equation was reformulated as an optimization problem for the dynamic signal control. The evaluation of the dynamic signal control system was carried out using a calibrated VISSIM microsimulation model. Python programming was used to integrate the dynamic signal control algorithm through the COM interface in VISSIM. The results indicated a good degree of improvement in overall average intersection delay of 12.6% compared to fixed time signal control. Thus, the proposed optimization method using delay from RFID sensors is suitable for implementing dynamic signal control under mixed traffic conditions.