Introducing probability in Colorwave

Technical Repor

Evaluation Criteria for Reader-to-Reader Anti-collision Protocols

Technical Repor

On Improving Automation by Integrating RFID in the Traceability Management of the Agri-Food Sector

Traceability is a key factor for the agri-food sector. RFID technology, widely adopted for supply chain management, can be used effectively for the traceability management. In this paper, a framework for the evaluation of a traceability system for the agri-food industry is presented and the automation level in an RFID-based traceability system is analyzed and compared with respect to traditional ones. Internal and external traceability are both considered and formalized, in order to classify different environments, according to their automation level. Traceability systems used in a sample sector are experimentally analyzed, showing that by using RFID technology, agri-food enterprises increase their automation level and also their efficiency, in a sustainable wa

Probabilistic DCS: An RFID reader-to-reader anti-collision protocol

The wide adoption of radio frequency identification (RFID) for applications requiring a large number of tags and readers makes critical the reader-to-reader collision problem. Various anti-collision protocols have been proposed, but the majority require considerable additional resources and costs. Distributed color system (DCS) is a state-of-the-art protocol based on time division, without noteworthy additional requirements. This paper presents the probabilistic DCS (PDCS) reader-to-reader anti-collision protocol which employs probabilistic collision resolution. Differently from previous time division protocols, PDCS allows multichannel transmissions, according to international RFID regulations. A theoretical analysis is provided in order to clearly identify the behavior of the additional parameter representing the probability. The proposed protocol maintains the features of DCS, achieving more efficiency. Theoretical analysis demonstrates that the number of reader-to-reader collisions after a slot change is decreased by over 30%. The simulation analysis validates the theoretical results, and shows that PDCS reaches better performance than state-of-the-art reader-to-reader anti-collision protocol

An algorithmic and architectural study on Montgomery exponentiation in RNS

The modular exponentiation on large numbers is computationally intensive. An effective way for performing this operation consists in using Montgomery exponentiation in the Residue Number System (RNS). This paper presents an algorithmic and architectural study of such exponentiation approach. From the algorithmic point of view, new and state-of-the-art opportunities that come from the reorganization of operations and precomputations are considered. From the architectural perspective, the design opportunities offered by well-known computer arithmetic techniques are studied, with the aim of developing an efficient arithmetic cell architecture. Furthermore, since the use of efficient RNS bases with a low Hamming weight are being considered with ever more interest, four additional cell architectures specifically tailored to these bases are developed and the tradeoff between benefits and drawbacks is carefully explored. An overall comparison among all the considered algorithmic approaches and cell architectures is presented, with the aim of providing the reader with an extensive overview of the Montgomery exponentiation opportunities in RNS

Tampering in RFID: A Survey on Risks and Defenses

RFID is a well-known pervasive technology, which provides promising opportunities for the implementation of new services and for the improvement of traditional ones. However, pervasive environments require strong efforts on all the aspects of information security. Notably, RFID passive tags are exposed to attacks, since strict limitations affect the security techniques for this technology. A critical threat for RFIDbased information systems is represented by data tampering, which corresponds to the malicious alteration of data recorded in the tag memory. The aim of this paper is to describe the characteristics and the effects of data tampering in RFID-based information systems, and to survey the approaches proposed by the research community to protect against it. The most important recent studies on privacy and security for RFID-based systems are examined, and the protection given against tampering is evaluated. This paper provides readers with an exhaustive overview on risks and defenses against data tampering, highlighting RFID weak spots and open issues

Agri-Food Traceability Management using a RFID System with Privacy Protection

In this paper an agri-food traceability system based on public key cryptography and Radio Frequency Identification (RFID) technology is proposed. In order to guarantee safety in food, an efficient tracking and tracing system is required. RFID devices allow recording all useful information for traceability directly on the commodity. The security issues are discussed and two different methods based on public cryptography are proposed and evaluated. The first algorithm uses a nested RSA based structure to improve security, while the second also provides authenticity of data. An experimental analysis demonstrated that the proposed system is well suitable on PDAs to

Investigation of interference models for RFID systems

The reader-to-reader collision in an RFID system is a challenging problem for communications technology. In order to model the interference between RFID readers, different interference models have been proposed, mainly based on two approaches: single and additive interference. The former only considers the interference from one reader within a certain range, whereas the latter takes into account the sum of all of the simultaneous interferences in order to emulate a more realistic behavior. Although the difference between the two approaches has been theoretically analyzed in previous research, their effects on the estimated performance of the reader-to-reader anti-collision protocols have not yet been investigated. In this paper, the influence of the interference model on the anti-collision protocols is studied by simulating a representative state-of-the-art protocol. The results presented in this paper highlight that the use of additive models, although more computationally intensive, is mandatory to improve the performance of anti-collision protocols

Trade-off between maximum cardinality of collision sets and accuracy of RFID reader-to-reader collision detection

As the adoption of the radio-frequency identification (RFID) technology is increasing, many applications require a dense reader deployment. In such environments, reader-to-reader interference becomes a critical problem, so the proposal of effective anti-collision algorithms and their analysis are particularly important. Existing reader-to-reader anti-collision algorithms are typically analyzed using single interference models that consider only direct collisions. The additive interference models, which consider the sum of interferences, are more accurate but require more computational effort. The goal of this paper is to find the difference in accuracy between single and additive interference models and how many interference components should be considered in additive models. An in-depth analysis evaluates to which extent the number of the additive components in a possible collision affects the accuracy of collision detection. The results of the investigation shows that an analysis limited to direct collisions cannot reach a satisfactory accuracy, but the collisions generated by the addition of the interferences from a large number of readers do not affect significantly the detection of RFID reader-to-reader collisions

Nonlinear predictive threshold model for real-time abnormal gait detection

Falls are critical events for human health due to the associated risk of physical and psychological injuries. Several fall related systems have been developed in order to reduce injuries. Among them, fall-risk prediction systems are one of the most promising approaches, as they strive to predict a fall before its occurrence. A category of fall-risk prediction systems evaluates balance and muscle strength through some clinical functional assessment tests, while other prediction systems investigate the recognition of abnormal gait patterns to predict a fall in real-time. The main contribution of this paper is a nonlinear model of user gait in combination with a threshold-based classification in order to recognize abnormal gait patterns with low complexity and high accuracy. In addition, a dataset with realistic parameters is prepared to simulate abnormal walks and to evaluate fall prediction methods. The accelerometer and gyroscope sensors available in a smartphone have been exploited to create the dataset. The proposed approach has been implemented and compared with the state-of-the-art approaches showing that it is able to predict an abnormal walk with a higher accuracy (93.5%) and a higher efficiency (up to 3.5 faster) than other feasible approaches