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This paper provides a comparative analysis of AES (Advanced Encryption Standard) and Salsa20 algorithm implementations, focusing on power consumption efficiency in passive RFID (radio-frequency identification) tags and ultra-low-power devices. The main objective of this work is to determine which of these algorithms is more suitable to operate in these types of devices. For this purpose, ASIC (application-specific integrated circuit) implementations of AES and Salsa20 based on low-power approaches were developed and their power consumption was evaluated. The results demonstrate that Salsa20 power consumption is lower than AES (about 17%), indicating that Salsa20 is a much better choice than AES for passive RFID tags.

This paper provides a comparative analysis of AES (Advanced Encryption Standard) and Salsa20 algorithm implementations, focusing on power consumption efficiency in passive RFID (radio-frequency identification) tags and ultra-low-power devices. The main objective of this work is to determine which of these algorithms is more suitable to operate in these types of devices. For this purpose, ASIC (application-specific integrated circuit) implementations of AES and Salsa20 based on low-power approaches were developed and their power consumption was evaluated. The results demonstrate that Salsa20 power consumption is lower than AES (about 17%), indicating that Salsa20 is a much better choice than AES for passive RFID tags. [ABSTRACT FROM AUTHOR]

Due to busy schedules and a lack of tracking of food that is stored, a lot of food is wasted every day in households. According to the UNEP Food Waste Index Report 2021, India's household food waste amounts to 50 kg per person per year, or over 68 million tons. In 2023, India would have produced over 68 million tons of food waste. Food waste is rising quickly every year. The following variables will affect food loss and waste (FLW) at the consumer level: improper food storage, including not using it before it goes bad. Partially used ingredients, preparing meals beyond necessity, and poor visibility of food in freezers are the main causes of food spoiling at home. According to data from the Food Safety and Standards Authority of India (FSSAI), one-third of India's food is wasted or spoils before it is eaten. This can be minimized by tracking food in smart containers, which work for both packed and unpacked food. This can be used with or without a refrigerator. [ABSTRACT FROM AUTHOR]

Abstract For successful animal husbandry, farmers need to monitor the health status of animals on a daily basis, as well as ensure the safety and protection of animals. In this regard, the problem of choosing the optimal system for monitoring the condition of farm animals in the modern market is urgent. The practical value of the scientific article is to analyze the problems of stakeholders and, based on the needs, conduct a comparative analysis of various modern systems for monitoring the condition of small cattle using the weighted sum method. The object of the study was the process of monitoring the condition of small cattle using RFID tags, as well as the ability to monitor their health depending on the chosen approach. The subject of the study was a livestock enterprise that raises small cattle. It was found that the health of small cattle directly affects the financial stability of the farm. In the presented study, the authors analyze the problems of stakeholders and, based on the needs of stakeholders, conduct a comparative analysis of various modern systems for monitoring the condition of small cattle using the weighted sum method. The results obtained will help farmers make informed decisions in the future when choosing the most appropriate monitoring option for more effective and high-quality monitoring of the condition of small cattle, thereby reducing the risk of diseases and increasing profits for companies.

Today, the primary issues for both physical and online retailers are fake and stolen goods. The likelihood that this product is fake is unknown to consumers. They lack a clear method to check the product’s integrity. This not only jeopardizes consumer trust but also imposes significant financial ramifications on both buyers and sellers. Therefore, we suggest a method in which we incorporate blockchain technology to confirm the product’s integrity. Central to our proposition is the integration of Non-Fungible Tokens (NFTs) as unique digital identifiers, combined with the dual security layers of holographic labels and RFID tags. This system operates on a private blockchain, ensuring enhanced scalability and transaction efficiency. Furthermore, the mechanism incorporates a collateral system initiated upon order placement, incentivizing honesty and timely delivery among participants. In the event of discrepancies, a robust dispute resolution system, underpinned by a voting mechanism, ensures fairness and trustworthiness. Our experimental implementation demonstrates the system’s effectiveness in reducing costs and enhancing transparency in supply chain management. The results highlight the potential of blockchain technology in revolutionizing supply chain management, offering a compelling alternative to traditional systems with reduced costs and increased security and transparency.

Achieving efficient warehouse operations for product management in an indoor environment has recently become a challenging issue. If a user can store a product in a vacant place and then roughly localize the product with a simple system, this localization system will enable efficient and flexible area usage in a warehouse. Complex radio wave propagation phenomena also make indoor localization more challenging. This paper introduces a radio frequency identification (RFID) system to localize products in indoor environments, including warehouses and cold storage. This approach uses distributed directional reference RFID tags in the areas as product location beacons, enabling received signal strength indicator (RSSI) measurements reflecting information on distances and directions for determining product coordinates. A user with a handheld reader stands in the close vicinity of the product. Then, the user reads the surrounding reference RFID tags for collecting the RSSI data. The use of machine learning (ML) addresses unstable user behaviors and unexpected acquired RSSI variations due to wireless propagation. Regression and classification algorithms in ML estimate product locations. The experimental demonstrations in actual indoor environments validate the proposed localization method. The experimental environments measure $24 \,m \times 12 \,m$ in a conference room and $9 \,m \times 12 \,m$ in a laboratory room. Experimental results show that this approach can provide localization accuracy of less than 2 meters, with wide application potential in inventory management and product tracking in various indoor environments, including factories, warehouses, and cold storage.

A platform-tolerant RFID (Radio-Frequency Identification) tag is presented, designed to operate across the entire RFID band. This tag utilizes a small Artificial Magnetic Conductor (AMC) structure as a shielding element for an ungrounded RFID tag antenna. It can be easily mounted on various surfaces, including low permittivity dielectric materials, metal objects, or even attached to the human body for wearable applications. The key features of this RFID tag include its ability to be tuned within the worldwide RFID band, achieving a maximum theoretical read range of over 11 m. Despite its advanced capabilities, the design emphasizes simplicity and cost-effective manufacturing. The design and simulations were conducted using CST Studio Suite. [ABSTRACT FROM AUTHOR]

Copyright of Brazilian Journal of Biology is the property of Instituto Internacional de Ecologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to busy schedules and a lack of tracking of food that is stored, a lot of food is wasted every day in households. According to the UNEP Food Waste Index Report 2021, India’s household food waste amounts to 50 kg per person per year, or over 68 million tons. In 2023, India would have produced over 68 million tons of food waste. Food waste is rising quickly every year. The following variables will affect food loss and waste (FLW) at the consumer level: improper food storage, including not using it before it goes bad. Partially used ingredients, preparing meals beyond necessity, and poor visibility of food in freezers are the main causes of food spoiling at home. According to data from the Food Safety and Standards Authority of India (FSSAI), one-third of India’s food is wasted or spoils before it is eaten. This can be minimized by tracking food in smart containers, which work for both packed and unpacked food. This can be used with or without a refrigerator.

In the realm of sustainable IoT and AI applications for the well-being of elderly individuals living alone in their homes, falls can have severe consequences. These consequences include post-fall complications and extended periods of immobility on the floor. Researchers have been exploring various techniques for fall detection over the past decade, and this study introduces an innovative Elder Fall Detection system that harnesses IoT and AI technologies. In our IoT configuration, we integrate RFID tags into smart carpets along with RFID readers to identify falls among the elderly population. To simulate fall events, we conducted experiments with 13 participants. In these experiments, RFID tags embedded in the smart carpets transmit signals to RFID readers, effectively distinguishing signals from fall events and regular movements. When a fall is detected, the system activates a green signal, triggers an alarm, and sends notifications to alert caregivers or family members. To enhance the precision of fall detection, we employed various machine and deep learning classifiers, including Random Forest (RF), XGBoost, Gated Recurrent Units (GRUs), Logistic Regression (LGR), and K-Nearest Neighbors (KNN), to analyze the collected dataset. Results show that the Random Forest algorithm achieves a 43% accuracy rate, GRUs exhibit a 44% accuracy rate, and XGBoost achieves a 33% accuracy rate. Remarkably, KNN outperforms the others with an exceptional accuracy rate of 99%. This research aims to propose an efficient fall detection framework that significantly contributes to enhancing the safety and overall well-being of independently living elderly individuals. It aligns with the principles of sustainability in IoT and AI applications. [ABSTRACT FROM AUTHOR]

Chipless radio-frequency identification (RFID) sensors are not yet widespread in practical applications because of their limited sensitivity and selectivity when compared to more mature sensing technologies. The search for a suitable material to perform the sensing function has often been focused on the most common materials used in electrochemical sensing approaches, but little work has been done to directly relate the performances of chipless or microwave sensors to the characteristics of the materials used to fabricate them. In this work we are simulating the impact of the substrate material on the performances of a chipless RFID sensor for humidity detection. The dielectric parameters of the substrate material turn out to be very important to maximize the sensor performances, in relation to the operative range of the sensor (based on the desired application) and to the effective dielectric properties of the sensitive material used, we verify the simulated results with measurements of real chipless humidity cells with Nafion 117 sensitive material. We show which types of substrate are preferable for low-humidity detection and which substrates' features are instead fundamental to operate in a wider humidity range. [ABSTRACT FROM AUTHOR]

Nowadays, supermarkets are almost developed with much technological advancement. People purchase different items from the supermarkets and put them into a trolley because it's the simplest method employed in supermarkets to hold goods. However, throughout the entire process of shopping, customer must push the trolley manually by their own effort and when it involves the billing process customers must wait in long queues to pay their bills. this can be a time-wasting process because of the busy schedule of individuals. So, to avoid this our project presents development of the smart shopping trolley (SST) that may be integrated into the smart mall system. The SST can provide customers with the efficient interface so the shopping service are often effectively done. With the utilization of radiofrequency identification (RFID) tags, the SST can automatically detect the assorted products which are being added within the cart and show the related information on the computer program (LCD and webserver). Finally, the automated billing service is done by the SST and therefore the stored shopping data are going to be transmitted to the net or cloud server of mall through ESP8266. So, the proposed SST interacts with the customer and provides efficient shopping service. [ABSTRACT FROM AUTHOR]

Objective: To evaluate a novel technology for real time tracking of RF-Identified (RFID) surgical tools (Biotic System), providing intraoperative data analytics during simulated cardiovascular procedures. Ineffective asset management in the Operating Room (OR) leads to inefficient utilization of resources and contributes to prolonged operative times and increased costs. Analysis of captured data can assist in quantifying instrument utilization, procedure flow, performance and prevention of retained instruments. Methods & Results: Five surgeons performed thirteen simulated surgical cases on three human cadavers. Procedures included (i) two abdominal aortic aneurysm (AAA) repairs, (ii) three carotid endarterectomies (CE), (iii) two femoropopliteal (fem-pop) bypasses, (iv) thoracic aortic aneurysm repair, (v) coronary artery bypass graft, (vi) aortic valve replacement, (vii) ascending aortic aneurysm repair, (viii) heart transplants, and (ix) mitral valve replacement. For each case an average of 139 surgical instruments were RFID-tagged and tracked intraoperatively. Data was captured and analyzed retrospectively. Of the 139 instruments tracked across each of the 13 cases, 55 instruments (39.5%) were actually used, demonstrating a high level of redundancy. For repeat cases (i.e. CE/AAA/fem-pop): (i) average instrument usage was 41 ± 3.6 (8.8% variation) for CE (n=3); (ii) average instrument usage was 69 ± 4.0 (5.8% variation) for AAA (n=2); and (iii) average instrument usage was 48 ± 2.5 (5.3% variation) for fem- pop (n=2). Results also showed a reduction in end-of-procedure instrument counting times of 58-87%. Conclusions: We report on a method for collecting intraoperative data analytics regarding instrument usage via RFID technology. This system will help refine instrument selection, quantitate instrument utilization and prevent inadvertent retention in a patient. This should help increase efficiency in packaging and sterilization and let surgeons make objective decisions in the composition of surgical trays. Clinical and Translational Impact Statement—Intraoperative analytics of surgical tools and associated equipment may ultimately lead to safer more efficient surgeries that increase patient outcomes while decreasing the cost of care.

In this work, a UHF broadband surface-independent textile fully woven radio frequency identification (RFID) tag is presented. The antenna is composed of two stacked multilayer fabric pieces in which the shaped conductive and dielectric surfaces are part of the woven structure. In addition, a novel technique for the integration of the RFID chip in the woven structure was developed, providing a maximum integration level and making possible the manufacturing of the tag in a single step using conventional machinery from the textile industry. A tag prototype was experimentally characterized, showing a 12.5 m read range under a $\pm 60\,\, {}\times {}\pm 60^\circ $ angular range, when using a circularly polarized interrogator device with 35.2 dBm effective isotropic radiated power (EIRP). [ABSTRACT FROM AUTHOR]

This paper presents the design and analysis of an automated traffic signage inventory management system employing the radio-frequency identification (RFID) technology. Traffic signage inventory management faces the operational challenge of recognizing a large number of traffic signs spread in a large area without obvious identifications on them. Thanks to the remote sensing ability of RFID, the operational efficiency can be significantly improved by scanning traffic signs remotely in motion. The system consists of an in-vehicle RFID reader and a handheld RFID reader, both of which connect to mobile applications with user-friendly interfaces. Additionally, user-friendly control software and a database are developed. In this paper, the adequacy of the RFID technology for the task is assessed. On the theoretical side, this paper investigates the radio-wave propagation model and the antenna radiation range. Additionally, the influences of the vehicle speed and the sign-to-reader distance on the reading performance are studied and empirical tests of the tag positioning are conducted. Finally, a system protocol is validated by a field test. [ABSTRACT FROM AUTHOR]

Private cars’ travel has been one of the main factors causing urban traffic congestion. Especially during morning and evening rush hours, private car commuters bring a significant burden to traffic. However, there is very little literature on them due to the lack of access to relevant data. A real-world dataset containing vehicle passing records of Electronic Registration Identification (ERI) of vehicles provides us with an opportunity to research private car commuters. We propose a regular behavior-based model to recognize private car commuters. In the model, a regular behavior-based definition of private car commuters is firstly proposed. Then, TDSP(Time dependent shortest path)-based distance measurement and a hierarchical clustering method are designed to extract regular behaviors. Furthermore, we utilize a regular threshold $p $ to help determine regular behaviors. The experiment, which is conducted on a real-world dataset containing one-week vehicle passing records in Chongqing of China, validates the effectiveness and accuracy of the proposed model. Moreover, we analyze the mobility pattern of private car commuters, and some typical mobility patterns of them are successfully found. [ABSTRACT FROM AUTHOR]

Tag identification is a critical operation in large-scale RFID applications. Typically, in the RFID-enabled warehouse, the reader needs to execute tag identifications to obtain the inventory information of numerous tagged items. The existing schemes usually divide the time frame into multiple slots and map each tag to one of them for replying its identity. This imposes serious tag collisions because two or more tags may be mapped to the same slot and their responses corrupt with each other. When tag collision happens, all the collided tags cannot be identified by the reader, which significantly increases the identification delay. To overcome the collision problem in the identification process, this paper proposes a Group Tag Identification (GTI) framework to identify grouped tags in both singleton and collision slots. The key novelty of GTI is in leveraging tag-correlation to identify grouped tags in the collision slots without any extra transmission overhead. The main challenge of this work is to overcome the communication and architectural limitations of RFID systems in the context of building ID and slot-correlation between tags. Extensive simulations show that GTI significantly reduces the identification delay by up to 40 percent when compared with the state-of-the-art dynamical frame slotted aloha schemes. [ABSTRACT FROM AUTHOR]

In the last two decades, Radio Frequency Identification (RFID) technology has attained prominent performance improvement and has been recognized as one of the key enablers of the Internet of Things (IoT) concepts. In parallel, extensive employment of Machine Learning (ML) algorithms in diverse IoT areas has led to numerous advantages that increase successful utilization in different scenarios. The work presented in this paper provides a use-case feasibility analysis of the implementation of ML algorithms for the estimation of ALOHA-based frame size in the RIFD Gen2 system. Findings presented in this research indicate that the examined ML algorithms can be deployed on modern state-of-the-art resource-constrained microcontrollers enhancing system throughput. In addition, such utilization can cope with latency since the execution time is sufficient to meet protocol needs. [ABSTRACT FROM AUTHOR]

A multitag detection technique is proposed for frequency-coded chipless radio frequency identification (RFID) to achieve minimum separations of tags, enhanced data capacity, and calibration-free features. Previous attempts for multitag detection include signal processing, comparisons with a database, and space-division multiple access (SDMA); nevertheless, these techniques rise to the challenges of large separations of tags, reduced capacity, and the complexity due to a phased array or beamforming technology, respectively. In contrast, the proposed technique overcomes these limitations by a new framework that integrates signal processing and SDMA. The capability is derived from the independent component analysis (ICA), which transforms mixing backscattering fields into an optimization model; by using the Newton method to maximize non-Gaussianity, the original resonances of each tag can be recovered. Furthermore, the proposed technique eliminates the procedure of calibration. An 8 bit system is designed and tested over 2.0–5.0 GHz. When two tags are separated by 0, 10, and 20 mm, ICA shows average reliability of 80.4%, 90.4%, and 91.5%, respectively. Thus, closely adjacent tags can be detected without calibration even for a high-density system. Real-world implementation issues, including four-tag detection, orientation mismatch, and a displacement of tags, are also analyzed to validate the proposed technique. [ABSTRACT FROM AUTHOR]

Packaging has become a broad field of development of different technologies that evolve, offering possibilities for manufacturers to position themselves in an increasingly demanding market. The demand for smart packaging offers an added value to the logistics in the supply chain and the final recipient. Nevertheless, a systematic literature review is required to evidence the opportunities that smart packaging provides such as functionalities regarding the case of fruits and vegetables that exhibit the greatest percentages of waste at the production stage. In this category, non-climacteric fruits start to perish at the recollection stage, and thus, the processes that follow must be controlled and monitored to prevent and reduce waste. In the present study, a search is carried out for definitions, typologies, and applications of functional packaging for the fresh unprocessed food sector, identifying the most developed technologies for those classified as active and intelligent. Databases such as Scopus and Science Direct and the search engine of Google Scholar were consulted. Four main fields of study were identified: food preservation, supply chain, printed electronics, and biopolymers. Hence, it is expected to promote possibilities for the research and development of technologies for smart packaging, to contribute with proposals in the design and manufacturing fields according to the needs of the local agricultural industry. [ABSTRACT FROM AUTHOR]

The ground plane has never been considered as a degree of freedom to be used for chipless radio frequency (RF) identification (RFID) tag design purposes. For the first time, we show that the interaction with the ground plane can be exploited to achieve challenging designs, such as depolarizing tag insensitive to orientation (i.e., nonzero cross polar for any roll angle). The principle relies on the perturbation of the ground plane symmetry with merely one microstrip dipole placed near the edge of the substrate. Chipless RFID tags are realized using three different shapes of the substrate (square, octagonal, and circular) to achieve multiple edges. The measurements are performed in a semianechoic and office environment with tag attached to objects (cardboard box and metallic plate). The measured results of the square chipless RFID tags present magnitude variations (< 10 dB) but are detectable over a full 360° even in real environment yielding an “orientation-insensitive” detection system. Compared to previous designs, the frequency variability of the peaks is negligible. [ABSTRACT FROM AUTHOR]

The vehicle localization, which aims to identify a vehicle and then position the vehicle with a high precision, can be used to facilitate various applications and services in vehicular networks. Unfortunately, conventional localization systems, e.g., global positioning system (GPS), hardly meet the accuracy requirements especially in certain specific scenarios, such as tunnels. At the same time, Ultrahigh frequency (UHF) radio frequency identification (RFID) has become an efficient booster for internet of things (IoT) due to the desirable advantages, such as low cost, battery-free, and unique identification. In this paper, based on the UHF-RFID, we propose a novel real-time vehicle localization scheme in GPS-Less Environments. Considering the practical implementation of multiple RFID reader antennas on a vehicle is constrained, we adopt single antenna multi-frequency ranging scheme, in which the integer ambiguity problem is solved by the maximum-likelihood estimation (MLE)-based robust Chinese remainder theorem (CRT). With the reconstructed distances between the tags and the reader, the coordinates of the vehicle then can be calculated with the Levenberg-Marquardt (LM) algorithm. Furthermore, the computational complexities of the algorithms and the time consumption of the proposed scheme are analyzed. The experimental results demonstrate that the proposed scheme can track vehicle’s location with error lower than 27 cm at the probability of 90%. [ABSTRACT FROM AUTHOR]

RFID (Radio Frequency Identification) is a crucial application technology in the Internet of Things (IoT) technology. The IoT terminal device needs to be authenticated before accessing the IoT network in order to avoid security holes. Due to the limited resources of the tag side in passive RFID systems, ultra-lightweight RFID authentication protocols are often used in such systems. Based on the characteristics of the ultra-lightweight authentication protocol, we propose a safe and efficient mutual authentication protocol which uses only bitwise operation including XOR and circular left-rotation operation. Cryptanalysis shows that the proposed protocol can prevent many known attacks and has better security performance than some existing ultra-lightweight protocols. In addition, performance evaluation shows that the proposed protocol performs better than the existing ultra-lightweight protocols in terms of computational cost, storage requirement and communication cost. [ABSTRACT FROM AUTHOR]

Chipless RFID tag decoding has some inherent degrees of uncertainty because there is no handshake protocol between chipless tags and readers. This article initially compares the outcome of different pattern recognition methods to decode some frequency-based tags in the mm-wave spectrum. It will be shown that these pattern recognition methods suffer from almost 2%–5% false decoding rate. To overcome this misdecoding problem, two novel methods of making images of the chipless tags are presented. The first method is making 2-D images based on side-looking aperture radar concepts, and the second one is making virtual 2-D images from the 1-D backscattering signals. Then, a 2-D decoding algorithm is suggested based on a convolutional neural network to decode those tag images and compare the results. It is shown that this combined decoding method has very high accuracy, and it almost eliminates any ambiguity and false decoding problems. This is the first time a deep learning method is used with image construction methods to decode chipless RFID tags. [ABSTRACT FROM AUTHOR]

The first article in a series of five papers devoted to hydrogen energy digitalization. The article discusses the prospects of hydrogen energy use as an alternative to fossil fuels, the objectives of using hydrogen as an energy source, and the problems that arise with it. Methods for obtaining energy from hydrogen without accompanying adverse emissions into the environment are described. The impact of the economy digitalization on production processes, as well as the most popular digital technologies and their role in hydrogen energy are shown. The digital processes available and currently being implemented, as well as promising, developing technologies for the transition to digitalization, are presented. [ABSTRACT FROM AUTHOR]

A novel low-profile (<0.005 λ) jigsaw-shaped metasurface for platform-tolerant nested-slot radio frequency identification (RFID) tag antenna is proposed in this letter. It consists of a 4 × 4 array of rippled-edged patch units with a central through-via. Compared with the widely used patch-unit artificial magnetic conductor structure, the proposed jigsaw-shaped metasurface is proved to suppress the surface waves effectively and reflect the electromagnetic waves in phase in the industrial scientific medical band of 902–928 MHz, therefore, it could improve the frequency and radiation stability of the nested slot RFID tag antenna on different platforms, and enhance the radiation performance of the tag antenna. The prototype of the metasurface was fabricated and measured as an interlayer of the nested-slot RFID tag and different platforms. The measured operation frequency band remains stable, and the measured reading range has a range deviation of less than 8.7% on different platforms. [ABSTRACT FROM AUTHOR]

This work presents a Self Sovereign Identity based system proposal to show how Blockchain, Building Information Modeling, Internet of Thing devices, and Self Sovereign Identity concepts can support the process of building digitalization, guaranteeing the compliance standards and technical regulations. The proposal ensures eligibility, transparency and traceability of all information produced by stakeholders, or generated by IoT devices appropriately placed, during the entire life cycle of a building artifact. By exploiting the concepts of the Self Sovereign Identity, our proposal allows the identification of all involved stakeholders, the storage off-chain of all information, and that on-chain of the sole data necessary for the information notarization and certification, adopting multi-signature approval mechanisms where appropriate. In addition it allows the eligibility verification of the certificated information, providing also useful information for facility management. It is proposed as an innovative system and companies that adopt the Open Innovation paradigm might want to pursue it. The model proposal is designed exploiting the Veramo platform, hence the Ethereum Blockchain, and all the recommendations about Self Sovereign Identity systems given by the European Blockchain Partnership, and by the World Wide Web Consortium. [ABSTRACT FROM AUTHOR]

Radio frequency identification (RFID) has been widely applied in large-scale applications such as logistics, merchandise and transportation. However, it is still a technical challenge to effectively estimate the number of tags in complex mobile environments. Most of existing tag identification protocols assume that readers and tags remain stationary throughout the whole identification process and ideal channel assumptions are typically considered between them. Hence, conventional algorithms may fail in mobile scenarios with unreliable channels. In this paper, we propose a novel RFID anti-collision algorithm for tag identification considering path loss. Based on a probabilistic identification model, we derive the collision, empty and success probabilities in a mobile RFID environment, which will be used to define the cardinality estimation method and the optimal frame length. Both simulation and experimental results of the proposed solution show noticeable performance improvement over the commercial solutions. [ABSTRACT FROM AUTHOR]

Copyright of Buletinul AGIR is the property of Asociatia Generala a Inginerilor din Romania and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

RFID tagssee a widespread use in modern security systems, including home intercoms, access control cards, contactless credit cards, biometric passports. Here we focus on a single application, namely access control systems. Currently they have either high cost or low security guarantees. Hence, the developments focusing on improving access control security while lowering the cost is a rapidly developing field. The purpose of this work is to create an alternative access control scheme, where card scanners are replaced with passive RFID tags, and all of the communication is done via user’s smartphone Wi-Fi. Based on the analysis of existing approaches to the development of access control systems, it was concluded that use of mobile systems is the most promising due to their expandability and presence of a large number of sensors, such as NFC, camera etc. In the proposed model RFID tags are mounted near a turnstile or a smart door. Tag reading and programming is done via NFC chip directly on an Android or iOS mobile device, which allows for a significant price cut for such a system implementation. A detailed description of a tag writing procedure with the data required to perform it is provided. To enhance security, together with smartphone-based authorization we require the user to provide his photograph while entering a secure gate. The photograph is then displayed on a monitoring dashboard side-by-side with his registration picture, so that the two can then be matched against each other. The developed client-server application offers administrative system used to configure gate access policies and monitor entrances with filters by access time, user and gate. Besides that, we propose a mobile application that allows gate registration and serves as a door unlock key. The access control model that we suggest reduces installation costs required, as it is fully wireless and uses cheap autonomous RFID-tags as its main component. We expect the presented application to be easy in adaptation to customer needs and to existing security systems.