Analysis of Tag Loss Ratio in dynamic RFID systems

Abstract. Radio Frequency Identification (RFID) systems promise a revolution in logistics and inventory applications. By means of wireless communication, a master device can detect and identify nearby electronic tags. Traditionally, the performance of RFID systems and their identification protocols has been analyzed for static configurations, that is, without considering incoming or outgoing tags, but just a fixed number of initially unidentified tags. However, many real scenarios cannot be consistently modeled that way. In this work we introduce a Markov model which allows us to study a dynamic RFID tag scenario, where a flow of tags is considered. This model can be used to compute the Tag Loss Ratio, which measures the ratio of outgoing unidentified tags to the incoming tags in the system, which is a critical metric in dynamic configurations. The analysis is carried out for two families of protocols used as medium access control in RFID, Framed Slotted Aloha and non-persistent CSMA. With the aim of validating the analysis predictions, we get simulation results, by means of a simulator. We evaluate a scenario similar to a real application, i.e. a mail control system based on RFID

Ambient Intelligence Systems for Personalized Sport Training

Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project “Ambient Intelligence Systems Support for Athletes with Specific Profiles”, which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes’ mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.). Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.). Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes’ training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, where the objective is to maintain the heart rate (HR) of the runner in a target range. For each track, the environmental conditions (temperature of the next track), the current athlete condition (HR), and the intrinsic difficulty of the track (slopes) influence the performance of the athlete. The decision engine, implemented by means of (m; s)-splines interpolation, estimates the future HR and selects the best track in each fork of the circuit. This method achieves a success ratio in the order of 80%. Indeed, results demonstrate that if environmental information is not take into account to derive training orders, the success ratio is reduced notably.Ministerio de Educación y Ciencia; DEP2006-56158-C03-01/02/03Ministerio de Educación y Ciencia; TEC2007-67966 -01/02/TCM CON-PARTE-1/2Ministerio de Industria, Turismo y Comercio ; TSI-020301-2008-16 ELISAMinisterio de Industria, Turismo y Comercio ; TSI-020301-2008-2 PIRAmID

Longer and less overlapping food webs in anthropogenically disturbed marine ecosystems: confirmations from the past

The human exploitation of marine resources is characterised by the preferential removal of the largest species. Although this is expected to modify the structure of food webs, we have a relatively poor understanding of the potential consequences of such alteration. Here, we take advantage of a collection of ancient consumer tissues, using stable isotope analysis and SIBER to assess changes in the structure of coastal marine food webs in the South-western Atlantic through the second half of the Holocene as a result of the sequential exploitation of marine resources by hunter-gatherers, western sealers and modern fishermen. Samples were collected from shell middens and museums. Shells of both modern and archaeological intertidal herbivorous molluscs were used to reconstruct changes in the stable isotopic baseline, while modern and archaeological bones of the South American sea lion Otaria flavescens, South American fur seal Arctocephalus australis and Magellanic penguin Spheniscus magellanicus were used to analyse changes in the structure of the community of top predators. We found that ancient food webs were shorter, more redundant and more overlapping than current ones, both in northern-central Patagonia and southern Patagonia. These surprising results may be best explained by the huge impact of western sealing on pinnipeds during the fur trade period, rather than the impact of fishing on fish populations. As a consequence, the populations of pinnipeds at the end of the sealing period were likely well below the ecosystem's carrying capacity, which resulted in a release of intraspecific competition and a shift towards larger and higher trophic level prey. This in turn led to longer and less overlapping food webs

LBTM: Listen-before-Talk Protocol for Multiclass UHF RFID Networks

Radio Frequency Identification (RFID) is considered one of the pioneering technologies of the Internet of Things (IoT). It allows to bind physical environments to information processing systems, adding new capabilities like automatic inventorying, location, or sensing with batteryless tags. Indeed, many data flows of physical objects can be tracked using this technology, and it is common to find heterogeneous traffics present in the same facility, each managed by different sets of readers. For example, in a grocery store, typically we have two kinds of readers: those carrying out a continuous inventory, whose goal is knowing the contents of the shelves as accurately as possible; and a set of checking-out readers at exit gates for the billing process that has to minimize the waiting time of customers. Another example of multiclass traffic is a hospital, where new families of sensing tags allow staff to wirelessly monitor patients—which obviously must be done as a priority—and coexist with other readers aimed at precisely knowing the location of equipment or drugs. Even with the same goal, there could be readers requiring different setups, for example in the hospital case, readers located at doors for inventorying purposes have a short time available to identify passing-by objects or people, and thus they have to work with a higher priority than regular readers performing inventorying tasks. In this work, we investigate a modification of the standard listen-before-talk (LBT) protocol for RFID networks which can support this kind of multipriority environment, by offering different qualities of service to each traffic. Results demonstrate that by tuning the protocol setup, it is possible to establish a trade-off between the performance of each traffic. This is shown for the two cited examples, the grocery shop and the hospital, using a simulation tool allowing us to implement a full-scale RFID model. In addition, we present a greedy mechanism for online reader setup. Instead of selecting offline a hard priority level, this greedy algorithm is able to adapt the priority to achieve the required quality-of-service (QoS) level