When Mobile Phones are RFID-Equipped - Finding E.U.-U.S. Solutions to Protect Consumer Privacy and Facilitate Mobile Commerce

New mobile phones have been designed to include delivery of mobile advertising and other useful location-based services, but have they also been designed to protect consumers\u27 privacy? One of the key enabling technologies for these new types of phones and new mobile services is Radio Frequency Identification (RFID), a wireless communication technology that enables the unique identification of tagged objects. In the case of RFID-enabled mobile phones, the personal nature of the devices makes it very likely that, by locating a phone, businesses will also be able to locate its owner. Consumers are currently testing new RFID-enabled phones around the globe, but the phones are not yet in general use by consumers in the United States and Europe. The incorporation of RFID into cell phones in order to deliver mobile advertising and other location-based services raises a host of important privacy questions that urgently need to be addressed before the phones become widely available. Analyzing the risks to consumer privacy in this new context, this paper offers a comparative law analysis of the applicable regulatory frameworks and recent policy developments in the European Union and the United States and concludes that there are many privacy concerns not presently addressed by E.U. and U.S. laws. This article also offers specific ideas to protect consumers\u27 privacy through applications of fair information practices and privacy-enhancing technologies. When mobile phones are RFID-equipped, consumers will need new privacy protections in order to understand the risks and make knowledgeable decisions about their privacy

Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

Smart cities: event everywhere

The research attempts to provide a big picture from the literature through a Systematic Literature Review about the smart city and the existing standards topics for interchanging data through Smart City Apps. Additionally a prototype was created to analyze one of the standards found in the SL

zCap: a zero configuration adaptive paging and mobility management mechanism

Today, cellular networks rely on fixed collections of cells (tracking areas) for user equipment localisation. Locating users within these areas involves broadcast search (paging), which consumes radio bandwidth but reduces the user equipment signalling required for mobility management. Tracking areas are today manually configured, hard to adapt to local mobility and influence the load on several key resources in the network. We propose a decentralised and self-adaptive approach to mobility management based on a probabilistic model of local mobility. By estimating the parameters of this model from observations of user mobility collected online, we obtain a dynamic model from which we construct local neighbourhoods of cells where we are most likely to locate user equipment. We propose to replace the static tracking areas of current systems with neighbourhoods local to each cell. The model is also used to derive a multi-phase paging scheme, where the division of neighbourhood cells into consecutive phases balances response times and paging cost. The complete mechanism requires no manual tracking area configuration and performs localisation efficiently in terms of signalling and response times. Detailed simulations show that significant potential gains in localisation effi- ciency are possible while eliminating manual configuration of mobility management parameters. Variants of the proposal can be implemented within current (LTE) standards

Droid Jacket: sistema de monitorização móvel de uma equipa

Mestrado em Engenharia dos Computadores e TelemáticaOs profissionais de emergência lidam no seu quotidiano com situações de perigo, agindo muitas vezes sob pressão, expondo-se a níveis de stress e fadiga por períodos extensos, causando um impacto negativo nas suas vidas e saúde. Neste contexto, a utilização de novas soluções a partir de tecnologias vestíveis, redes de sensores e dispositivos móveis cria a oportunidade de oferecer um acompanhamento mais próximo, com o objectivo de detectar situações de perigo e dar suporte a equipas de profissionais de emergência médica em campo. No entanto, existem muito poucas soluções voltadas para a utilização sinérgica destas tecnologias emergentes que dêem suporte integrado a monitorização de uma equipa. Nesta dissertação propomos uma arquitectura conceptual de software (TeamMonitor) para agregação, análise e disseminação de informação direccionada para a monitorização de equipas na acção. Team Monitor e sustentada na noção de nós de coordenação centrais, que são responsáveis pela recolha de dados de diferentes fontes (ex.: vários profissionais de emergência) e subsequente fluxos de trabalho para análise, incluindo processamento básico de dados (ex.: execução de detectores de alarmes de sinal biológico) e troca eficiente de dados com clientes externos. O nó central dissocia a rede de tecnologias de informação da rede de fornecimento de dados. O suporte é dado pela camada de aquisição de sinal biológico e de análise que nós desenvolvemos, o módulo BIOSal. De modo a ilustrar a viabilidade do TeamMonitor, nós implementámos um sistema como prova do conceito, o Droid Jacket, onde o nó central da TeamMonitor e instanciado num dispositivo móvel com Android. Droid Jacket permite monitorizar até quatro Vital Jacket (uma tecnologia vestível para a monitorização de uma pessoa), fornecendo tanto o suporte para a troca e ficiente dos sinais agregados para clientes externos, como a detec ção precoce de potenciais alarmes a partir do processamento em tempo real dos dados adquiridos. Ao contr ario de outras abordagens comuns, nós consideramos as capacidades de processamento do dispositivo móvel para estação base. Nós implementámos um algoritmo simples de detecção do complexo QRS da onda cardíaca e de arritmias no Droid Jacket, a partir do electrocardiograma adquirido pelas unidades com o Vital Jacket vestido. Droid Jacket demonstra que a incorporação de dispositivos móveis num cenáario de monitorização de uma equipa é uma opção razoável, e o conceito pode ser estendido e adaptado a cenários mais realistas como a monitorização de bombeiros.First responders deal in their daily lives with danger, working under pressure, exposing themselves to stress and fatigue for extended periods, which has a negative impact on their lives and health. In this context, using new solutions based on wearable technologies, sensor networks and mobile devices raises the opportunity to provide closer monitoring, aiming at detecting hazard conditions and supporting rst responder teams in the eld. However, very few solutions exist addressing such synergistic use of these emergent technologies to support integrated team monitoring. In this dissertation we propose a conceptual software architecture (TeamMonitor) for information aggregation, analysis and dissemination towards eld-action teams monitoring. TeamMonitor is supported in the notion of central coordination nodes that are responsible for data aggregation from multiple sources (e.g.: several rst responders professionals) and subsequent analysis work ows, including basic data processing (e.g.: running biosignal alarms detectors) and data stream relay to external clients. The central node decouples the IT network from the data providers network. This support is provided by a biosignal acquisition and analysis framework we developed, the BIOSal module. To illustrate TeamMonitor feasibility, we implemented a proof-ofconcept application, the DroidJacket, in which the TeamMonitor central node is instantiated in an Android mobile device. DroidJacket is able to monitor up to four VitalJacket R devices (a wearable garment for individual monitoring) providing both the support to relay the aggregated signals data to remote clients and an early detection of potential alarms based on real-time processing of the acquired data. Unlike other common approaches, we rely on the mobile device processing capabilities for the base-station. We implemented a basic algorithm for heart wave QRS complex and arrhythmia detection in DroidJacket, using the electrocardiogram acquired from the VitalJacket units. DroidJacket demonstrates that incorporating mobile devices in the team monitoring scenario is a reasonable option nowadays and the concept can be extended and adapted to more realistic scenarios like re ghter monitoring

Ambient Lighting Integrated Assistance System

This work aims to provide a personalized wireless ambient lighting for assistance environments. The main idea is to use an ambient lighting as a communication channel and as health support system. Knowledge from circadian rhythm and colored lighting will be used to provide an improved self-healing environment. Other functionalities include the reaction to external events captured by sensors, changing the lighting status in order to serve as a visual communication and notification channel, readily understood. The development of such a tool is composed by the development of 4 essential sub-parts: 1) Android app for the user defined settings such as types of external events and their visual notifications, as well as the activation of predefined lighting configurations; 2) Web application for programming complex user defined lighting scenes and configurations; 3) Web server that provides the services necessary for the user, getting and storing user settings and lighting status as well as command light bulbs actions from external events or circadian rhythm updates, 4) Database where all the user defined settings and lighting status are stored.In the future, the tool can also allow to put in practice and test existing theories and studies about lighting, colors and circadian rhythm effects on humans.This work aims to provide a personalized wireless ambient lighting for assistance environments. The main idea is to use an ambient lighting as a communication channel and as health support system. Knowledge from circadian rhythm and colored lighting will be used to provide an improved self-healing environment. Other functionalities include the reaction to external events captured by sensors, changing the lighting status in order to serve as a visual communication and notification channel, readily understood. The development of such a tool is composed by the development of 4 essential sub-parts: 1) Android app for the user defined settings such as types of external events and their visual notifications, as well as the activation of predefined lighting configurations; 2) Web application for programming complex user defined lighting scenes and configurations; 3) Web server that provides the services necessary for the user, getting and storing user settings and lighting status as well as command light bulbs actions from external events or circadian rhythm updates, 4) Database where all the user defined settings and lighting status are stored.In the future, the tool can also allow to put in practice and test existing theories and studies about lighting, colors and circadian rhythm effects on humans

Internet of Things Applications - From Research and Innovation to Market Deployment

The book aims to provide a broad overview of various topics of Internet of Things from the research, innovation and development priorities to enabling technologies, nanoelectronics, cyber physical systems, architecture, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from technology to international cooperation and the global "state of play".The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level. Internet of Things is creating a revolutionary new paradigm, with opportunities in every industry from Health Care, Pharmaceuticals, Food and Beverage, Agriculture, Computer, Electronics Telecommunications, Automotive, Aeronautics, Transportation Energy and Retail to apply the massive potential of the IoT to achieving real-world solutions. The beneficiaries will include as well semiconductor companies, device and product companies, infrastructure software companies, application software companies, consulting companies, telecommunication and cloud service providers. IoT will create new revenues annually for these stakeholders, and potentially create substantial market share shakeups due to increased technology competition. The IoT will fuel technology innovation by creating the means for machines to communicate many different types of information with one another while contributing in the increased value of information created by the number of interconnections among things and the transformation of the processed information into knowledge shared into the Internet of Everything. The success of IoT depends strongly on enabling technology development, market acceptance and standardization, which provides interoperability, compatibility, reliability, and effective operations on a global scale. The connected devices are part of ecosystems connecting people, processes, data, and things which are communicating in the cloud using the increased storage and computing power and pushing for standardization of communication and metadata. In this context security, privacy, safety, trust have to be address by the product manufacturers through the life cycle of their products from design to the support processes. The IoT developments address the whole IoT spectrum - from devices at the edge to cloud and datacentres on the backend and everything in between, through ecosystems are created by industry, research and application stakeholders that enable real-world use cases to accelerate the Internet of Things and establish open interoperability standards and common architectures for IoT solutions. Enabling technologies such as nanoelectronics, sensors/actuators, cyber-physical systems, intelligent device management, smart gateways, telematics, smart network infrastructure, cloud computing and software technologies will create new products, new services, new interfaces by creating smart environments and smart spaces with applications ranging from Smart Cities, smart transport, buildings, energy, grid, to smart health and life. Technical topics discussed in the book include: • Introduction• Internet of Things Strategic Research and Innovation Agenda• Internet of Things in the industrial context: Time for deployment.• Integration of heterogeneous smart objects, applications and services• Evolution from device to semantic and business interoperability• Software define and virtualization of network resources• Innovation through interoperability and standardisation when everything is connected anytime at anyplace• Dynamic context-aware scalable and trust-based IoT Security, Privacy framework• Federated Cloud service management and the Internet of Things• Internet of Things Application

Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqa

Recurrence quantification analysis is a widely used method for characterizing patterns in time series. This article presents a comprehensive survey for conducting a wide range of recurrence-based analyses to quantify the dynamical structure of single and multivariate time series, and to capture coupling properties underlying leader-follower relationships. The basics of recurrence quantification analysis (RQA) and all its variants are formally introduced step-by-step from the simplest autorecurrence to the most advanced multivariate case. Importantly, we show how such RQA methods can be deployed under a single computational framework in R using a substantially renewed version our crqa 2.0 package. This package includes implementations of several recent advances in recurrence-based analysis, among them applications to multivariate data, and improved entropy calculations for categorical data. We show concrete applications of our package to example data, together with a detailed description of its functions and some guidelines on their usage

Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqa

Recurrence quantification analysis is a widely used method for characterizing patterns in time series. This article presents a comprehensive survey for conducting a wide range of recurrence-based analyses to quantify the dynamical structure of single and multivariate time series, and to capture coupling properties underlying leader-follower relationships. The basics of recurrence quantification analysis (RQA) and all its variants are formally introduced step-by-step from the simplest auto-recurrence to the most advanced multivariate case. Importantly, we show how such RQA methods can be deployed under a single computational framework in R using a substantially renewed version our crqa 2.0 package. This package includes implementations of several recent advances in recurrence-based analysis, among them applications to multivariate data, and improved entropy calculations for categorical data. We show concrete applications of our package to example data, together with a detailed description of its functions and some guidelines on their usage.Comment: Describes R package crqa v. 2.0: https://cran.r-project.org/web/packages/crqa