IEEE Pervasive Computing (IEEE PERVAS COMPUT )

Publisher: IEEE Computer Society; IEEE Communications Society, Institute of Electrical and Electronics Engineers

Description

  • Impact factor
    2.06
    Show impact factor history
     
    Impact factor
  • 5-year impact
    2.57
  • Cited half-life
    7.00
  • Immediacy index
    0.19
  • Eigenfactor
    0.00
  • Article influence
    1.11
  • Website
    IEEE Pervasive Computing Magazine website
  • Other titles
    IEEE pervasive computing, Institute of Electrical and Electronics Engineers pervasive computing, Pervasive computing
  • ISSN
    1536-1268
  • OCLC
    47360632
  • Material type
    Periodical, Internet resource
  • Document type
    Journal / Magazine / Newspaper, Internet Resource

Publisher details

Institute of Electrical and Electronics Engineers

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on Author's personal website, employers website or publicly accessible server
    • Author's post-print on Author's server or Institutional server
    • Author's pre-print must be removed upon publication of final version and replaced with either full citation to IEEE work with a Digital Object Identifier or link to article abstract in IEEE Xplore or replaced with Authors post-print
    • Author's pre-print must be accompanied with set-phrase, once submitted to IEEE for publication ("This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible")
    • Author's pre-print must be accompanied with set-phrase, when accepted by IEEE for publication ("(c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")
    • IEEE must be informed as to the electronic address of the pre-print
    • If funding rules apply authors may post Author's post-print version in funder's designated repository
    • Author's Post-print - Publisher copyright and source must be acknowledged with citation (see above set statement)
    • Author's Post-print - Must link to publisher version with DOI
    • Publisher's version/PDF cannot be used
    • Publisher copyright and source must be acknowledged
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Impaired driver alertness increases the likelihood of drivers’ making mistakes and reacting too late to unexpected events while driving. This is particularly a concern on monotonous roads, where a driver’s attention can decrease rapidly. While effective countermeasures do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behavior in real-time. The aim of this study is to predict drivers’ level of alertness through surrogate measures collected from in-vehicle sensors. Electroencephalographic activity is used as a reference to evaluate alertness. Based on a sample of 25 drivers, data was collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device. Various classification models were tested from linear regressions to Bayesians and data mining techniques. Results indicated that Neural Networks were the most efficient model in detecting lapses in alertness. Findings also show that reduced alertness can be predicted up to 5 minutes in advance with 90% accuracy, using surrogate measures such as time to line crossing, blink frequency and skin conductance level. Such a method could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring, in real-time, drivers' behavior on highways.
    IEEE Pervasive Computing 10/2014;
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    ABSTRACT: Infotainment applications can provide new business opportunities when they're used in vehicular networks. However, these applications are challenging by nature, and a testing platform is required to validate that they work properly. Existing simulation platforms focus mainly on providing a testing framework for safety applications that don't require infrastructure. To address this, the Vehicular Emulations Platform for Real Applications (Vespa) was developed to allow for experiments with many vehicles running real-world applications with real-time requirements in complex network scenarios. To demonstrate Vespa's usefulness, a use case on the performance of video-streaming applications is offered. In this use case, the applications are tested in highway conditions in which packet losses occur due to network layer handoffs.
    IEEE Pervasive Computing 07/2014; 13(3):58-66.
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    ABSTRACT: Despite significant advances in context sensing and inference since its inception in the late 1990s, context-aware computing still doesn't implement a holistic view of all covert aspects of the user state. Here, the authors introduce the concept of cognitive context as an extension to the current notion of context with a cognitive dimension. They argue that visual behavior and brain activity are two promising sensing modalities for assessing the cognitive context and thus the development of cognition-aware computing systems.
    IEEE Pervasive Computing 07/2014; 13(3):80-83.
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    ABSTRACT: This article discusses how digital fabrication affects the production of electronic devices, drawing on the author's experience making radios, speakers, mice, and cellphones. Several case studies demonstrate the differences between digital fabrication and traditional mass-production or do-it-yourself (DIY) practices. The author analyzes how the digital nature of design files and the flexibility of fabricating them into physical objects transform the design and production of enclosures and circuit boards, but has less effect on component sourcing, circuit assembly, and programming. The author also explores how different people can get involved in the process of fabricating devices, the skills required, and relevant motivations. This article is part of a special issue on printing and fabrication.
    IEEE Pervasive Computing 07/2014; 13(3):22-29.
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    ABSTRACT: Transantiago, the smartcard-based public transportation system in Santiago, Chile, includes both a subway system and buses. An online information system lets card holders find detailed trip information, including start time and location, as well as frequency and type of transportation used, by simply providing its card ID. This article studies the privacy implications of the availability of the Transantiago online information system. The authors explore how much of a card holder's information and behavior could be extracted from something as simple as their card ID. They concluded that, given that the corresponding card IDs are known, they can use simple statistical techniques to correctly predict the nearest public transport station to the homes of more than half of the users. This article is part of a special issue on pervasive analytics and citizen science.
    IEEE Pervasive Computing 05/2014; 13(2):37--43.
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    ABSTRACT: Smart handheld tools epitomize a mythical and technological quest for personal mastery of skill, delivering both might and mind in the hands of their holders. A recent spur of academic and industrial efforts has given rise to a new field of research in HCI, one devoted to smart handheld tools. Here, the authors offer a definition for smart handheld tools, discuss the tools' origins and motivation, and present a survey of prominent work by themselves and others in disciplines such as fabrication, painting, printing, and maintenance. They also discuss their experiences operating in this new territory and conclude with a vision of a hybrid creative practice: smart handheld instruments that enable synergetic cooperation with human skill, personal style, and computational assistance that results in accuracy, guidance, and protection for users. This article is part of a special issue on printing and fabrication.
    IEEE Pervasive Computing 01/2014; 13(3):48-57.
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    ABSTRACT: This overview of RFID in underground mining service applications is set against the backdrop of the major challenges this technology must overcome for successful implementation in rugged environments. It also considers future prospects of RFID in the mining industry.
    IEEE Pervasive Computing 01/2014; 13(1):72-79.
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    ABSTRACT: The recently developed conductive inkjet printing process enables conductive circuits to be created quickly, cheaply, and easily using a consumer-grade inkjet printer. In its basic form, the technique supports a single layer of wiring on a flexible substrate. This can be a valuable tool for pervasive computing research because it allows simple electronic circuits and devices to be built and iterated quickly, in an analogous manner to the use of 3D printers for prototyping mechanical structures. It is possible to rapidly create touch- and proximity-sensitive surfaces, to cut and fold the printed conductive patterns, and to augment them with off-the-shelf electronic components and custom-made subcircuits. The authors present the possibilities enabled by conductive inkjet printing, bringing together their previously published results and presenting their latest insights and findings. They consider these printing and fabrication techniques as a suite of tools for researchers and practitioners who wish to fabricate a variety of functional device prototypes. They aim to enable others to understand the strengths, weaknesses, and applicability of conductive inkjet printing across a range of pervasive computing applications. This article is part of a special issue on printing and fabrication.
    IEEE Pervasive Computing 01/2014; 13(3):30-38.
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    ABSTRACT: Systematically and quantitatively determining patterns in consumer flow is an important problem in marketing research. Identifying these patterns can facilitate an understanding of where and when consumers purchase products and services at physical retail shops. Collecting data on real consumers who shop at retail stores is one of the most challenging and expensive aspects of these studies. This article introduces ConvenienceProbe, a phone-based data collection system for retail trade-area analysis. The proposed method targets local residents shopping at neighborhood convenience stores. This study deploys and tests the system by collecting real customer flow data in neighborhood convenience stores. Results show that the consumer flow data collected from the ConvenienceProbe system is comparable to that from a traditional face-to-face interview method.
    IEEE Pervasive Computing 01/2014; 13(1):64-71.
  • Source
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    ABSTRACT: Smart health devices monitor certain health parameters, are connected to an Internet service, and target primarily a lay consumer seeking a healthy lifestyle rather than the medical expert or the chronically ill person. These devices offer tremendous opportunities for wellbeing and self-management of health. This department reviews smart health devices from a pervasive computing perspective, discussing various devices and their functionality, limitations, and potential.
    IEEE Pervasive Computing 01/2014; 13(2):10-13.
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    ABSTRACT: Smartphones have emerged as ubiquitous devices that are being used to host a rich array of pervasive apps in diverse areas, including healthcare, gaming, and social networking. A key requirement of many of these apps is that they keep their mobile users up-to-date as changes occur in some subject of interest. One way of providing timely updates to smartphone apps is to use push notification technology. In this article, the authors identify design issues for push notification systems and reveal underlying concepts for the notification channels that bind mobile devices to push services. They describe five service offerings and report on the performance of their channels based on an empirical study.
    IEEE Pervasive Computing 01/2014; 13(2):61-71.
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    ABSTRACT: Improvements in health behavior theory will be central to creating successful interventions that encourage and support behavior change and maintenance. The authors discuss dynamic, multimethod, conceptually driven, and data-rich approaches for the development of testable computational models of health-related behaviors in real time.
    IEEE Pervasive Computing 01/2014; 13(3):13-17.
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    ABSTRACT: The Facilitating Interactions for Dogs with Occupations (FIDO) project in the Animal Interaction Lab at Georgia Tech aims to facilitate communication between working dogs and their handlers. Here, the authors discuss their research on testing a working dog's ability to perform distinct tasks in response to vibrations at different points on their body.
    IEEE Pervasive Computing 01/2014; 13(2):80-83.
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    ABSTRACT: Supply-chain RFID systems introduce significant privacy issues to consumers, making it necessary to encrypt communications. Because the resources available on tags are very small, it is generally assumed that only symmetric-key cryptography can be used in such systems. Unfortunately, symmetric-key cryptography imposes negative trust issues between the various stake-holders, and risks compromising the security of the whole system if even a single tag is reverse engineered. This work presents a working prototype implementation of a secure RFID system which uses public-key cryptography to simplify deployment, reduce trust issues between the supply-chain owner and tag manufacturer, and protect user privacy. The authors' prototype system consists of a UHF tag running custom firmware, a standard off-the-shelf reader and custom point-of-sale terminal software. No modifications were made to the reader or the air interface, proving that high-security EPC tags and standard EPC tags can coexist and share the same infrastructure.
    IEEE Pervasive Computing 01/2014; 13(2):52-60.
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    ABSTRACT: This article compares two rate-control approaches that a cloud messaging service can use to deliver notifications for a variety of applications. The author reviews the pros and cons of the two approaches in terms of metrics such as latency, fairness, and overhead related to carrier network signaling and battery life of the user device.
    IEEE Pervasive Computing 01/2014; 13(1):84-88.
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    ABSTRACT: The 15th Workshop on Mobile Computing Systems and Applications (HotMobile 2014) was had over 90 attendees participating in two days of presentations and lively discussion. Learn about each of the sessions and prevalent themes throughout.
    IEEE Pervasive Computing 01/2014; 13(3):84-87.
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    ABSTRACT: This special issue aims to explore critical elements of the overall design, user experience, and resulting solutions related to using pervasive computing technologies to inform our understanding of the dynamics of ourselves and our ecosystem, community, and urban landscapes. This issue not only explores pervasive technologies but also reviews practical solutions for improving citizens' health, wellbeing, and everyday lives. Careful attention is also paid to the interplay of social media within this landscape of pervasive analytics and citizen science.
    IEEE Pervasive Computing 01/2014; 13(2):18-19.
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    ABSTRACT: Research has shown a relationship between the physical characteristics of a city neighborhood (such as the presence of playgrounds and fast-food outlets) and neighborhood deprivation as defined in socioeconomic indices. Official land-use data has often been the source for such research. This article examines the viability of using social-networking data as an alternative source. The authors study all venues on the Foursquare location-mapping application across a variety of London census areas. They study the relationship between the presence of different venues in an area and its score on the socioeconomic Index of Multiple Deprivation. They conclude that knowing which venues are hosted by which community offers not only insights into neighborhood deprivation but also a reasonable way of predicting community deprivation scores at fine-grained temporal resolutions. This article is part of a special issue on pervasive analytics and citizen science.
    IEEE Pervasive Computing 01/2014; 13(2):30-36.