From research to classroom a course in pervasive computing

In a nutshell, the course is basically about emerging, visible and invisible computing systems and devices. Pervasive computing has many names, including ubiquitous computing, and its key element is the omnipresence of information devices. These devices can be embedded into cars, airplanes, ships, bikes, posters, signboards, walls, and even clothes. The course therefore focuses on independent information devices, including wearable computers, mobile phones, screen phones, and PDAs, and the services made available by them. It includes the study of computer and network architectures for pervasive computing, mobile computing, human-computer interaction using speech and vision, pervasive software systems, and experimental pervasive computing systems.     

Bayesian on-line spectral change point detection: a soft computing approach for on-line ASR

Current automatic speech recognition (ASR) works in off-line mode and needs prior knowledge of the stationary or quasi-stationary test conditions for expected word recognition accuracy. These requirements limit the application of ASR for real-world applications where test conditions are highly non-stationary and are not known a priori. This paper presents an innovative frame dynamic rapid adaptation and noise compensation technique for tracking highly non-stationary noises and its application for on-line ASR. The proposed algorithm is based on a soft computing model using Bayesian on-line inference for spectral change point detection (BOSCPD) in unknown non-stationary noises. BOSCPD is tested with the MCRA noise tracking technique for on-line rapid environmental change learning in different non-stationary noise scenarios. The test results show that the proposed BOSCPD technique reduces the delay in spectral change point detection significantly compared to the baseline MCRA and its derivatives. The proposed BOSCPD soft computing model is tested for joint additive and channel distortions compensation (JAC)-based on-line ASR in unknown test conditions using non-stationary noisy speech samples from the Aurora 2 speech database. The simulation results for the on-line AR show significant improvement in recognition accuracy compared to the baseline Aurora 2 distributed speech recognition (DSR) in batch-mode.     

Ubiquitous Access to Unified Messaging: A Study of Usability and the Use of Pervasive Computing

The advent of mobile devices and the wireless Internet is having a profound impact on the way people communicate, as well as on the user interaction paradigms used to access information that was traditionally accessible only through visual interfaces. Applications for mobile devices entail the integration of various data sources optimized for delivery to limited hardware resources and intermittently connected devices through wireless networks. Although telephone interfaces arise as one of the most prominent pervasive applications, they present interaction challenges such as the augmentation of speech recognition through natural language (NL) understanding and high-quality text-to-speech conversion. This article presents an experience in building an automated assistant that is natural to use and could become an alternative to a human assistant. The Mobile Assistant (MA) can read e-mail messages, book appointments, take phone messages, and provide access to personal-organizer information. Key components are a conversational interface, enterprise integration, and notifications tailored to user preferences. The focus of the research has been on supporting the pressing communication needs of mobile workers and overcoming technological hurdles such as achieving high accuracy speech recognition in noisy environments, NL understanding, and optimal message presentation on a variety of devices and modalities. The article outlines findings from the 2 broad field trials and lessons learned regarding the support of mobile workers with pervasive computing devices and emerging technologies.     

面向普适计算环境的Android平台服务编排框架

普适计算环境下的智能移动设备是面向终端用户的服务资源聚集和编排的主要载体。普适计算环境中的服务资源具有多种不同的形态,包括基于互联网提供的Web服务、终端设备自身服务和资源(例如本地应用、自带传感器)以及所处环境中可访问的服务(例如环境传感器)。此外,不断变化的上下文环境对软件本身的自适应能力提出了新的要求,而移动设备上的服务编排受设备计算能力和资源的限制。为了解决上述问题,提出了一个面向普适计算环境的Android平台服务编排框架ASOF。通过ASOF,移动终端可在运行时获取所需业务流程的服务模板,并对该模板中的抽象服务进行服务绑定,实现轻量级的混合服务编排,使终端能够动态获得调用普适计算环境中各种类型的服务的能力。随后,基于OSGi Felix框架给出了一套ASOF的标准实现,并以一个具体案例验证其有效性。     

基于普适计算的交互汉语学习系统

普适计算是一种正在兴起的新型的计算模式,其“无处不在,以人为本”的理念使得普适计算在许多领域的应用中都有着巨大的潜力。本文综合应用语音识别、声调识别、软交换、文语转换、语音邮件等多种技术,使用以人为中心的普适计算系统模型（HPC）和分层结构分析与设计方法（LAAD）,设计并实现了一个基于普适计算的交互汉语学习系统,该系统能够计算出汉语学习者发音的准确度和声调的准确度,并通过普适服务平台提供实时交互、学习情况自动收集等普适服务,为学习者建立起了一个良好的汉语学习环境,帮助他们高效、便捷地学习汉语。     

Smart devices and spaces for pervasive computing

Applications and services for pervasive computing have been dramatically grown and have contributed extensively to our daily experiences in recent years. Smart systems, devices, and spaces are proactive for ubiquitous and pervasive computing. Smart information technology (IT) is also an outcome of the state of the art and novel mobile and ubiquitous computing technologies that include highly capable handheld device, pervasive and personal device, etc. This special issue will be a trigger for further related research and technology improvements in pervasive and ubiquitous computing using smart devices and services. This special issue called for original papers describing the latest developments, trends, and solutions of smart devices and spaces for pervasive computing including real-time operating systems (OS), tiny OS and middleware supports, mobile system performance, trustworthy Internet and communications, agents and mobile and pervasive services, among others. In particular, this special issue focuses on a remote control and media-sharing system, flash storage-based smart system, heterogeneous mobile OS, and prediction and auto-execution system for pervasive computing.     

动态计算网络:一种面向物联网的普适计算框架

随着物联网的发展,大量不同的设备通过各种不同的方式连接到物联网中,使普适计算环境更加复杂和多样化,因此要求在物联网环境下的普适计算框架能适应新的计算条件的变化。提出了一种新的普适计算框架,以便在物联网环境中普适计算系统能够自动适应复杂多样的软硬件运行环境,使软件无需修改就可以在整个物联网环境中任意地执行,实现普适计算的服务发现、上下文感知与服务迁移功能。提出物联网环境下普适计算的基本运算单元为"动态计算网络",使用"设备动态匹配"作为普适计算软件自动适应环境的解决方案。提出的动态计算网络增强了普适计算软件对物联网环境的适应性,为面向物联网的通用软件系统设计提供了一种有效的解决方法。     

PICO: a middleware framework for pervasive computing

The pervasive information community organization is a framework for creating mission-oriented dynamic communities of autonomous software entities that perform tasks for users and devices. PICO's telemedicine example scenario demonstrates its potential as a simple, unique, and versatile middleware framework for pervasive computing.     

Automated speech recognition for spreadsheet tasks: Performance effects for experts and novices

The performance of spreadsheet users was compared for two modes of input to the computer, keyboard and automated speech recognition (ASR). Subjects from both an expert group and a novice group were also classified by decision style. Dependent measures were task completion time, accuracy, keystroke count, correction count, and user confidence. Results for a speaker‐dependent, discrete‐word recognizer showed that, for both simple data input and more complex analytical spreadsheet tasks, neither the experts nor the novices performed more effectively using ASR. However, both groups expressed the desirability of having speech input as an option for desktop computing.     

Motion does matter: an examination of speech-based text entry on the move

Desktop interaction solutions are often inappropriate for mobile devices due to small screen size and portability needs. Speech recognition can improve interactions by providing a relatively hands-free solution that can be used in various situations. While mobile systems are designed to be transportable, few have examined the effects of motion on mobile interactions. This paper investigates the effect of motion on automatic speech recognition (ASR) input for mobile devices. Speech recognition error rates (RER) have been examined with subjects walking or seated, while performing text input tasks and the effect of ASR enrollment conditions on RER. The obtained results suggest changes in user training of ASR systems for mobile and seated usage.     

PvcwCORBA:普适计算环境中间件的实现

针对普适环境的平台的多样性、资源的有限性、设备的移动性和应用高性能要求等需求，提出了其中间件的设计和实现方法，并据此构建了pvcwCORBA。通过试验验证了pvcwCORBA作为支持无线接入功能的高性能、嵌入式CORBA，能够适应普适计算环境的要求。     

一种面向普适计算的自适应软件平台的设计与实现

普适计算的适应性特征带来了有必要在软件平台层面解决的一系列共性问题,包括如何定义所支持的自适应软件体系结构、如何为上层应用的自适应提供必要的公共服务、如何使平台自身可以适应多维资源受限环境等。针对这些挑战,提出了对普适计算设备/资源进行适应性抽象的自主单元的概念,在此基础上给出了面向普适计算的自适应软件平台UbiStar的系统架构及其核心机制的设计与实现,并对UbiStar平台对适应性软件所提供的支持机制进行了概括,最后对相关工作进行了分析与比较。     

Diagnosing diabetes using neural networks on small mobile devices

Pervasive computing is often mentioned in the context of improving healthcare. This paper presents a novel approach for diagnosing diabetes using neural networks and pervasive healthcare computing technologies. The recent developments in small mobile devices and wireless communications provide a strong motivation to develop new software techniques and mobile services for pervasive healthcare computing. A distributed end-to-end pervasive healthcare system utilizing neural network computations for diagnosing illnesses was developed. This work presents the initial results for a simple client (patient’s PDA) and server (powerful desktop PC) two-tier pervasive healthcare architecture. The computations of neural network operations on both client and server sides and wireless network communications between them are optimized for real time use of pervasive healthcare services.     

Trust management in ubiquitous computing: A Bayesian approach

Designing a trust management scheme that can effectively evaluate the relationships among devices in pervasive computing environments is a challenging task. This paper continues the investigation of our recently proposed probabilistic trust management scheme for pervasive computing environments. We argue that in addition to allowing a device to find other appropriate devices with which to interact, while detecting those that are malicious, our trust management scheme is also capable of (1) allowing a device to judge the trustworthiness of another device it interacts with, while making a better use of the received recommendations and (2) behaving as expected when a device has little or enough experience of interactions with other devices and changes dynamically occur in the proportion of malicious devices. Simulation experiments are provided to assess the achievement of the stated goals, using some representative performance metrics.     

A novel approach to visualize web anomaly attacks in pervasive computing environment

These days, a pervasive computing environment is a rapidly changing trend towards increasingly always-on connected computing devices in the convergence environment. In a pervasive computing environment, there are various multimedia web services and communications for various devices in order to provide interesting and invaluable information to users. Meanwhile, providing a wide variety of the web-based multimedia services and communications may cause various security threats and abnormal behaviors. In this paper, a multimedia visualization approach for pervasive computing environment is proposed which analyzes HTTP request and response header information to detect and visualize multimedia web attacks based on the Bayesian method. We conducted a few cases’ experiment for the verification of the proposed approach in a real environment. The experimental results such as web attack detection visualization, scanning and password attack visualization, and attacker’s position tracking visualization verify the usability of the proposed approach.     

Algorithms for data-driven ASR parameter quantization

There is fast growing research on designing energy-efficient computational devices and applications running on them. As one of the most compelling applications for mobile devices, automatic speech recognition (ASR) requires new methods to allow it to use fewer computational and memory resources while still achieving a high level of accuracy. One way to achieve this is through parameter quantization. In this work, we compare a variety of novel sub-vector clustering procedures for ASR system parameter quantization. Specifically, we look at systematic data-driven sub-vector selection techniques, most of which are based on entropy minimization, and others on recognition accuracy maximization on a development set. We compare performance on two speech databases, phonebook, an isolated word speech recognition task, and timit, a phonetically diverse connected-word speech corpus. While the optimal entropy-minimizing or accuracy-driven quantization methods are intractable, several simple schemes including scalar quantization with separate codebooks per parameter and joint scalar quantization with normalization perform well in their attempt to approximate the optimal clustering.     

面向普适计算的服务构件动态部署问题及算法

有限的资源是嵌入式应用的一个局限性,因此越来越多的嵌入式设备联网,通过共享资源为用户提供灵活的服务以适应普适计算的要求.以构件化嵌入式操作系统Liquid为背景,研究普适计算环境下多个服务构件动态部署问题,合理分配利用资源,克服单个嵌入式设备的资源局限性.首先对部署问题进行描述,然后给出服务构件动态部署的基本算法和启发式算法,并对启发式算法优化,最后通过算法模拟及数据分析算法的性能.虽然在Liquid系统上进行模拟实现,但算法具有通用性,启发式算法的效率分析表明,它适合设备或者服务构件数目较多的普适计算环境,在部署服务构件的同时提高服务准入成功率和资源的利用率.     

普及计算环境的设备灵活接入技术研究--基于OSGi的数字家庭解决方案

普及计算使人们能通过各类智能计算设备，随时随地获得各种所需的信息服务。作为普及计算的一个重要的应用领域，数字家庭将家庭内各种家电和设备联网，通过网络为人们提供丰富、个性化、方便、安全和高效的服务。而如何达到各种智能设备的灵活接入，成了实现此目标的一个关键问题。在和。SVA-IBM联合实验室合作iHome项目中，作者对此进行了深入的研究。本文提出了基于OSGi的数字家庭普及计算环境智能计算设备灵活接入解决方案，并实现了一个应用的系统，从而验证其可行性。     

Dynamic Service Composition in Pervasive Computing

Service-oriented architectures (SOAs) promise to provide transparency to resource access by exposing the resources available as services. SOAs have been employed within pervasive computing systems to provide essential support to user tasks by creating services representing the available resources. The mechanism of combining two or more basic services into a possibly complex service is known as service composition. Existing solutions to service composition employ a template-matching approach, where the user needs are expressed as a request template, and through composition, a system would identify services to populate the entities within the request template. However, with the dynamism involved in pervasive environments, the user needs have to be met by exploiting available resources, even when an exact match does not exist. In this paper, we present a novel service composition mechanism for pervasive computing. We employ the service-oriented middleware platform called pervasive information communities organization (PICO) to model and represent resources as services. The proposed service composition mechanism models services as directed attributed graphs, maintains a repository of service graphs, and dynamically combines multiple basic services into complex services. Further, we present a hierarchical overlay structure created among the devices to exploit the resource unevenness, resulting in the capability of providing essential service-related support to resource-poor devices. Results of extensive simulation studies are presented to illustrate the suitability of the proposed mechanism in meeting the challenges of pervasive computing user mobility, heterogeneity, and the uncertain nature of involved resources.     

普适计算环境下的设备动态更新机制

普适计算应用中的设备是情境感知的载体和情境感知行为的执行者,起着关键性的作用。在一个持续运行的普适计算系统中,设备的损坏和更新是时有发生的,如何让用户以最小的代价完成设备的更新是该系统得以广泛应用的基础。本文在前期给出的基于OSGi/R-OSGi的普适计算框架基础上,提出了一种不需要系统开发人员介入的设备动态更新机制,以解决设备更新时存在的异构性问题。