Traceability is a key factor for the agri-food sector. Radio-frequency identification (RFID) technology, which is 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 traceabilities 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 way.

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.

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.

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 PM ${}_{10}$ and O ${}_3$ 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 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.