Dense passive radio frequency identification (RFID) systems are particularly susceptible to reader collision problems, categorized by reader-to-tag and reader-to-reader collisions. Both may degrade the system performance decreasing the number of identified tags per time unit. Although many proposals have been suggested to avoid or handle these collisions, most of them are not compatible with current standards and regulations, require extra hardware and do not make an efficient use of the network resources. This paper proposes the Geometric Distribution Reader Anti-collision (GDRA), a new centralized scheduler that exploits the Sift geometric probability distribution function to minimize reader collision problems. GDRA provides higher throughput than the state-of-the-art proposals for dense reader environments and, unlike the majority of previous works, GDRA is compliant with the EPCglobal standard and ETSI EN 302 208 regulation, and can be implemented in real RFID systems without extra hardware.Note to Practitioners -UHF RFID systems with multiple readers are commonly installed in many scenarios, where readers are placed in strategic places for checking specific areas. In these scenarios, the reader interferences occur and they can degrade the performance of our system. An efficient anticollision scheduler is necessary for avoiding and minimizing these interferences, and the current standards and regulations do not propose any efficient solution. In this work, a new scheduler is proposed to get the best performance of a typical UHF RFID system with multiple readers. Our proposal is compatible with the global standard and the current European regulations and is designed to be implemented in any commercial UHF reader in the market without extra hardware cost.Index Terms-EPCglobal, ETSI EN 302 208, reader collision problems, radio frequency identification (RFID, sift geometric distribution function.

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Northern Italy has one of the highest air pollution levels in the European Union. This paper describes a mobile wireless sensor network system intended to complement the already existing official air quality monitoring systems of the metropolitan town of Torino. The system is characterized by a high portability and low cost, in both acquisition and maintenance. The high portability of the system aims to improve the spatial distribution and resolution of the measurements from the official static monitoring stations. Commercial PM10 and O3 sensors were incorporated into the system and were subsequently tested in a controlled environment and in the field. The test in the field, performed in collaboration with the local environmental agency, revealed that the sensors can provide accurate data if properly calibrated and maintained. Further tests were carried out by mounting the system on bicycles in order to increase their mobility.

The majority of security systems for wireless sensor networks are based on symmetric encryption. The main open issue for these approaches concerns the establishment of symmetric keys. A promising key distribution technique is the random predistribution of secret keys. Despite its effectiveness, this approach presents considerable memory overheads, in contrast with the limited resources of wireless sensor networks. In this paper, an in-depth analytical study is conducted on the state-of-the-art key distribution schemes based on random predistribution. A new protocol, called q-s-composite, is proposed in order to exploit the best features of random predistribution and to improve it with lower requirements. The main novelties of q-s-composite are represented by the organization of the secret material that allows a storing reduction, by the proposed technique for pairwise key generation, and by the limited number of predistributed keys used in the generation of a pairwise key. A comparative analysis demonstrates that the proposed approach provides a higher level of security than the state-of-the-art schemes.

a b s t r a c tThe 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 protocols.

The reader-to-reader collision problem represents a research topic of great recent interest for the radio frequency identification (RFID) technology. Among the state-of-the-art anticollision protocols, the ones that provide high throughput often have special requirements, such as extra hardware. This study investigates new high throughput solutions for static RFID networks without additional requirements. In this paper, two contributions are presented: a new configuration, called Killer, and a new protocol, called distributed color noncooperative selection (DCNS). The proposed configuration generates selfish behavior, thereby increasing channel utilization and throughput. DCNS fully exploits the Killer configuration and provides new features, such as dynamic priority management, which modifies the performance of the RFID readers when it is requested. Simulations have been conducted in order to analyze the effects of the innovations proposed. The proposed approach is especially suitable for low-cost applications with a priority not uniformly distributed among readers. The experimental analysis has shown that DCNS provides a greater throughput than the state-of-the-art protocols, even those with additional requirements (e.g., 16 percent better than NFRA).

Injuries due to unintentional falls cause high social cost in which several systems have been developed to reduce them. Recently, two trends can be recognized. Firstly, the market is dominated by fall detection systems, which activate an alarm after a fall occurrence, but the focus is moving towards predicting and preventing a fall, as it is the most promising approach to avoid a fall injury. Secondly, personal devices, such as smartphones, are being exploited for implementing fall systems, because they are commonly carried by the user most of the day. This paper reviews various fall prediction and prevention systems, with a particular interest to the ones that can rely on the sensors embedded in a smartphone, i.e., accelerometer and gyroscope. Kinematic features obtained from the data collected from accelerometer and gyroscope have been evaluated in combination with different machine learning algorithms. An experimental analysis compares the evaluated approaches by evaluating their accuracy and ability to predict and prevent a fall. Results show that tilt features in combination with a decision tree algorithm present the best performance.

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