A Novel and Efficient Anti-Collision Protocol for RFID Tag Identification

Radio frequency identification (RFID) is prominent technology for fast object identification and tracking. In RFID systems, reader-to-reader or tag-to-tag collisions are common. Majority of probabilistic and deterministic anti-collisions methods are inefficient in channel distribution and improving the performance. In this work, simulation annealing based anti-collision protocol is proposed where there is uniform distribution of channels among readers. In addition, preference is given to tag state parameters over fixed scheduling in order to increase the performance. The tag state parameters named energy efficiency, distance from selected reader and distance from obstacles are considered. The simulation results show that the proposed approach is an effective mechanism where there is a minimum improvement of 16.7% for 100 readers and maximum of 32.7% for 1000 readers in tag identification ratio, and a minimum improvement of 23% for 1000 readers and maximum of 75.3% for 100 readers in total successful interrogation cycles. Further, total time cycles, total IDLE cycles, total number of collisions, delay, and total number of packets sent and received are reduced compared to state of-art protocols. It is observed that the proposed simulation annealing based protocol is contiguous channels allocation algorithm with zero collision

IGAA: An Efficient Optimization Technique for RFID Network Topology Design in Internet of Things

[[abstract]]Most RFID applications in the Internet of Things (IoTs) use multiple readers to read the IDs of multiple tags and form the RFID network. In such a network, unguarded reader deployment may generate over-crowded readers, cause interferences and, as a result, increases the deployment cost while degrading tag detection. Seeing that desirable reader deployment is crucial for RFID system performance, this paper introduces an optimization-based IGAA approach which outperforms existing RFID topology designs by turning up more favorable reader deployment and system performance. The new approach employs an advanced multi-objective fitness function and improved genetic annealing algorithms (GAA) to pursue a better RFID topology design. By involving an improved gene-stirring operation to help preserve good genes and locate optimal solutions for reader deployment, it is simple in operation but effective in practice. Experimental evaluation shows that when compared with related approaches, IGAA can yield better solution quality with less search time.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

Advances in analytical models and applications for RFID, WSN and AmI systems

Experimentos llevados a cabo con el equipo de división de honor UCAM Volleyball Murcia.[SPA] Internet de las cosas (IoT) integra distintos elementos que actúan tanto como fuentes, como sumideros de información, a diferencia de la percepción que se ha tenido hasta ahora de Internet, centrado en las personas. Los avances en IoT engloban un amplio número de áreas y tecnologías, desde la adquisición de información hasta el desarrollo de nuevos protocolos y aplicaciones. Un concepto clave que subyace en el concepto de IoT, es el procesamiento de forma inteligente y autónoma de los flujos de información que se dispone. En este trabajo, estudiamos tres aspectos diferentes de IoT. En primer lugar, nos centraremos en la infraestructura de obtención de datos. Entre las diferentes tecnologías de obtención de datos disponibles en los sistemas IoT, la Identificación por Radio Frecuencia (RFID) es considerada como una de las tecnologías predominantes. RFID es la tecnología detrás de aplicaciones tales como control de acceso, seguimiento y rastreo de contenedores, gestión de archivos, clasificación de equipaje o localización de equipos. Con el auge de la tecnología RFID, muchas instalaciones empiezan a requerir la presencia de múltiples lectores RFID que operan próximos entre sí y conjuntamente. A estos escenarios se les conoce como dense reader environments (DREs). La coexistencia de varios lectores operando simultáneamente puede causar graves problemas de interferencias en el proceso de identificación. Uno de los aspectos claves a resolver en los RFID DREs consiste en lograr la coordinación entre los lectores. Estos problemas de coordinación son tratados en detalle en esta tesis doctoral. Además, dentro del área de obtención de datos relativa a IoT, las Redes de Sensores Inalámbricas (WSNs) desempeñan un papel fundamental. Durante la última década, las WSNs han sido estudiadas ampliamente de forma teórica, y la mayoría de problemas relacionados con la comunicación en este tipo de redes se han conseguido resolver de forma favorable. Sin embargo, con la implementación de WSNs en proyectos reales, han surgido nuevos problemas, siendo uno de ellos el desarrollo de estrategias realistas para desplegar las WSN. En este trabajo se estudian diferentes métodos que resuelven este problema, centrándonos en distintos criterios de optimización, y analizando las diferentes ventajas e inconvenientes que se producen al buscar una solución equilibrada. Por último, la Inteligencia Ambiental (AmI) forma parte del desarrollo de aplicaciones inteligentes en IoT. Hasta ahora, han sido las personas quienes han tenido que adaptarse al entorno, en cambio, AmI persigue crear entornos de obtención de datos capaces de anticipar y apoyar las acciones de las personas. AmI se está introduciendo progresivamente en diversos entornos reales tales como el sector de la educación y la salud, en viviendas, etc. En esta tesis se introduce un sistema AmI orientado al deporte que busca mejorar el entrenamiento de los atletas, siendo el objetivo prioritario el desarrollo de un asistente capaz de proporcionar órdenes de entrenamiento, basadas tanto en el entorno como en el rendimiento de los atletas. [ENG] Internet of Things (IoT) is being built upon many different elements acting as sources and sinks of information, rather than the previous human-centric Internet conception. Developments in IoT include a vast set of fields ranging from data sensing, to development of new protocols and applications. Indeed, a key concept underlying in the conception of IoT is the smart and autonomous processing of the new huge data flows available. In this work, we aim to study three different aspects within IoT. First, we will focus on the sensing infrastructure. Among the different kind of sensing technologies available to IoT systems, Radio Frequency Identification (RFID) is widely considered one of the leading technologies. RFID is the enabling technology behind applications such as access control, tracking and tracing of containers, file management, baggage sorting or equipment location. With the grow up of RFID, many facilities require multiple RFID readers usually operating close to each other. These are known as Dense Reader Environments (DREs). The co-existence of several readers operating concurrently is known to cause severe interferences on the identification process. One of the key aspects to solve in RFID DREs is achieving proper coordination among readers. This is the focus of the first part of this doctoral thesis. Unlike previous works based on heuristics, we address this problem through an optimization-based approach. The goal is identifying the maximum mean number of tags while network constraints are met. To be able to formulate these optimization problems, we have obtained analytically the mean number of identifications in a bounded -discrete or continuous- time period, an additional novel contribution of our work. Results show that our approach is overwhelmingly better than previous known methods. Along sensing technologies of IoT, Wireless Sensor Networks (WSNs) plays a fundamental role. WSNs have been largely and theoretically studied in the past decade, and many of their initial problems related to communication aspects have been successfully solved. However, with the adoption of WSNs in real-life projects, new issues have arisen, being one of them the development of realistic strategies to deploy WSNs. We have studied different ways of solving this aspect by focusing on different optimality criteria and evaluating the different trade-offs that occur when a balanced solution must be selected. On the one hand, deterministic placements subject to conflicting goals have been addressed. Results can be obtained in the form of Pareto-frontiers, allowing proper solution selection. On the other hand, a number of situations correspond to deployments were the nodes¿ position is inherently random. We have analyzed these situations leading first to a theoretical model, which later has been particularized to a Moon WSN survey. Our work is the first considering a full model with realistic properties such as 3D topography, propellant consumptions or network lifetime and mass limitations. Furthermore, development of smart applications within IoT is the focus of the Ambient Intelligence (AmI) field. Rather than having people adapting to the surrounding environment, AmI pursues the development of sensitive environments able to anticipate support in people¿s actions. AmI is progressively being introduced in many real-life environments like education, homes, health and so forth. In this thesis we develop a sport-oriented AmI system designed to improve athletes training. The goal is developing an assistant able to provide real-time training orders based on both environment and athletes¿ biometry, which is aimed to control the aerobic and the technical-tactical training. Validation experiments with the honor league UCAM Volleyball Murcia team have shown the suitability of this approach.[ENG] Internet of Things (IoT) is being built upon many different elements acting as sources and sinks of information, rather than the previous human-centric Internet conception. Developments in IoT include a vast set of fields ranging from data sensing, to development of new protocols and applications. Indeed, a key concept underlying in the conception of IoT is the smart and autonomous processing of the new huge data flows available. In this work, we aim to study three different aspects within IoT. First, we will focus on the sensing infrastructure. Among the different kind of sensing technologies available to IoT systems, Radio Frequency Identification (RFID) is widely considered one of the leading technologies. RFID is the enabling technology behind applications such as access control, tracking and tracing of containers, file management, baggage sorting or equipment location. With the grow up of RFID, many facilities require multiple RFID readers usually operating close to each other. These are known as Dense Reader Environments (DREs). The co-existence of several readers operating concurrently is known to cause severe interferences on the identification process. One of the key aspects to solve in RFID DREs is achieving proper coordination among readers. This is the focus of the first part of this doctoral thesis. Unlike previous works based on heuristics, we address this problem through an optimization-based approach. The goal is identifying the maximum mean number of tags while network constraints are met. To be able to formulate these optimization problems, we have obtained analytically the mean number of identifications in a bounded -discrete or continuous- time period, an additional novel contribution of our work. Results show that our approach is overwhelmingly better than previous known methods. Along sensing technologies of IoT, Wireless Sensor Networks (WSNs) plays a fundamental role. WSNs have been largely and theoretically studied in the past decade, and many of their initial problems related to communication aspects have been successfully solved. However, with the adoption of WSNs in real-life projects, new issues have arisen, being one of them the development of realistic strategies to deploy WSNs. We have studied different ways of solving this aspect by focusing on different optimality criteria and evaluating the different trade-offs that occur when a balanced solution must be selected. On the one hand, deterministic placements subject to conflicting goals have been addressed. Results can be obtained in the form of Pareto-frontiers, allowing proper solution selection. On the other hand, a number of situations correspond to deployments were the nodes¿ position is inherently random. We have analyzed these situations leading first to a theoretical model, which later has been particularized to a Moon WSN survey. Our work is the first considering a full model with realistic properties such as 3D topography, propellant consumptions or network lifetime and mass limitations. Furthermore, development of smart applications within IoT is the focus of the Ambient Intelligence (AmI) field. Rather than having people adapting to the surrounding environment, AmI pursues the development of sensitive environments able to anticipate support in people¿s actions. AmI is progressively being introduced in many real-life environments like education, homes, health and so forth. In this thesis we develop a sport-oriented AmI system designed to improve athletes training. The goal is developing an assistant able to provide real-time training orders based on both environment and athletes¿ biometry, which is aimed to control the aerobic and the technical-tactical training. Validation experiments with the honor league UCAM Volleyball Murcia team have shown the suitability of this approach.Universidad Politécnica de CartagenaPrograma de doctorado en Tecnología de la Información y de las Comunicacione

Advanced Radio Frequency Identification Design and Applications

Radio Frequency Identification (RFID) is a modern wireless data transmission and reception technique for applications including automatic identification, asset tracking and security surveillance. This book focuses on the advances in RFID tag antenna and ASIC design, novel chipless RFID tag design, security protocol enhancements along with some novel applications of RFID

Decentralised Algorithms for Wireless Networks.

Designing and managing wireless networks is challenging for many reasons. Two of the most crucial in 802.11 wireless networks are: (a) variable per-user channel quality and (b) unplanned, ad-hoc deployment of the Access Points (APs). Regarding (a), a typical consequence is the selection, for each user, of a different bit-rate, based on the channel quality. This in turn causes the so-called performance “anomaly”, where the users with lower bit-rate transmit for most of the time, causing the higher bit-rate users to receive less time for transmission (air time). Regarding (b), an important issue is managing interference. This can be mitigated by selecting different channels for neighbouring APs, but needs to be carried out in a decentralised way because often APs belong to different administrative domains, or communication between APs is unfeasible. Tools for managing unplanned deployment are also becoming important for other small cell networks, such as femtocell networks, where decentralised allocation of scrambling codes is a key task

Wireless Sensors and their Applications in Controlling Vibrations

As wireless devices are becoming more powerful, more flexible and less costly to produce, they are often being applied in new ways. Combining wireless technology with new types of sensors results in the ability to monitor and control the environment in ways not previously possible. For example, an intelligent wireless sensor system that consists of a sensor, digital processor and a transceiver can be mounted on a board the size of a coin. The data collected by these devices are then transmitted to a central unit which is able to thoroughly process and store this data. Not only can the central processing station provide reports about certain physical parameters in the environment, it can also control the environment and other parameters of interest. The design process of these wireless sensor platforms is a well-developed area of research that covers concepts like networking, circuit design, Radio-Frequency (RF) circuits and antenna design. The design of a wireless sensor can be as simple as putting together a microcontroller, a transceiver and a sensor chip or as complicated as implementing all the necessary circuitry into a single integrated circuit. One of the main applications of the sensors is in a control loop which controls physical characteristics in an environment. Specifically, if the objective of a control system is to limit the amount of vibrations in a structure, vibration sensors such as accelerometers are usually used. In environments where the use of wires is costly or impossible, it makes sense to use wireless accelerometers instead. Among the numerous applications that can use such devices are the automotive and medical vibration control systems. In the automotive industry it is desirable to reduce the amount of vibrations in the vehicle felt by the passengers. These vibrations can originate from the engine or the uneven road, but they are damped using passive mechanical elements like rubber, springs and shocks. It is possible however, to have a more effective vibration suppression using active sensor-actuator systems. Since adding and maintaining wires in a vehicle is costly, a wireless accelerometer can be put to good use there. A medical application for wireless accelerometers can be used with a procedure called Deep Brain Stimulation (DBS). DBS is a relatively new and very effective treatment for advanced Parkinson’s disease. The purpose of DBS is to reduce tremors in the patients. In DBS a set of voltages is applied to the brain of the patient as some optimum combinations of voltages will have a very positive effect on the tremors. Those optimum voltages are currently found by trial and error while a doctor is observing the patient for tremors. Wireless accelerometers with the use of a computer algorithm can assist in this process by finding the optimum voltages using the feedback provided by the accelerometers. The algorithm will assist the doctor in making decisions and has the potential of finding the optimums completely on its own

Wireless Sensors and their Applications in Controlling Vibrations

As wireless devices are becoming more powerful, more flexible and less costly to produce, they are often being applied in new ways. Combining wireless technology with new types of sensors results in the ability to monitor and control the environment in ways not previously possible. For example, an intelligent wireless sensor system that consists of a sensor, digital processor and a transceiver can be mounted on a board the size of a coin. The data collected by these devices are then transmitted to a central unit which is able to thoroughly process and store this data. Not only can the central processing station provide reports about certain physical parameters in the environment, it can also control the environment and other parameters of interest. The design process of these wireless sensor platforms is a well-developed area of research that covers concepts like networking, circuit design, Radio-Frequency (RF) circuits and antenna design. The design of a wireless sensor can be as simple as putting together a microcontroller, a transceiver and a sensor chip or as complicated as implementing all the necessary circuitry into a single integrated circuit. One of the main applications of the sensors is in a control loop which controls physical characteristics in an environment. Specifically, if the objective of a control system is to limit the amount of vibrations in a structure, vibration sensors such as accelerometers are usually used. In environments where the use of wires is costly or impossible, it makes sense to use wireless accelerometers instead. Among the numerous applications that can use such devices are the automotive and medical vibration control systems. In the automotive industry it is desirable to reduce the amount of vibrations in the vehicle felt by the passengers. These vibrations can originate from the engine or the uneven road, but they are damped using passive mechanical elements like rubber, springs and shocks. It is possible however, to have a more effective vibration suppression using active sensor-actuator systems. Since adding and maintaining wires in a vehicle is costly, a wireless accelerometer can be put to good use there. A medical application for wireless accelerometers can be used with a procedure called Deep Brain Stimulation (DBS). DBS is a relatively new and very effective treatment for advanced Parkinson’s disease. The purpose of DBS is to reduce tremors in the patients. In DBS a set of voltages is applied to the brain of the patient as some optimum combinations of voltages will have a very positive effect on the tremors. Those optimum voltages are currently found by trial and error while a doctor is observing the patient for tremors. Wireless accelerometers with the use of a computer algorithm can assist in this process by finding the optimum voltages using the feedback provided by the accelerometers. The algorithm will assist the doctor in making decisions and has the potential of finding the optimums completely on its own

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Sensor-based ICT Systems for Smart Societies

L'abstract è presente nell'allegato / the abstract is in the attachmen