Predicting reduced driver alertness on monotonous highways : a driving simulator study

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.

Designing a mobile social tool that moderates drinking

A novel mobile social networking tool uses peer support to facilitate responsible drinking among young women. Focus group reports indicate that the tool���s design is easy to use and its functionalities would help peers reduce risk during drinking sessions.

I/O Device Virtualization in the multi-core era, a QoS perspective

In this paper, we propose an extension to the I/O device architecture, as recommended in the PCI-SIG IOV specification, for virtualizing network I/O devices. The aim is to enable fine-grained controls to a virtual machine on the I/O path of a shared device. The architecture allows native access of I/O devices to virtual machines and provides device level QoS hooks for controlling VM specific device usage. For evaluating the architecture we use layered queuing network (LQN) models. We implement the architecture and evaluate it using simulation techniques, on the LQN model, to demonstrate the benefits. With the architecture, the benefit for network I/O is 60% more than what can be expected on the existing architecture. Also, the proposed architecture improves scalability in terms of the number of virtual machines intending to share the I/O device.

Middleware for Mobile Sensing Applications in Urban Environments

Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.

Wireless Sensor Networks for Organizational Network Analysis

Since their emergence, wireless sensor networks (WSNs) have become increasingly popular in the pervasive computing industry. This is particularly true within the past five years, which has seen sensor networks being adapted for wide variety of applications. Most of these applications are restricted to ambience monitoring and military use, however, very few commercial sensor applications have been explored till date. For WSNs to be truly ubiquitous, many more commercial sensor applications are yet to be investigated. As an effort to probe for such an application, we explore the potential of using WSNs in the field of Organizational Network Analysis (ONA). In this short paper, we propose a WSN based framework for analyzing organizational networks. We describe the role of WSNs in learning relationships among the people of an organization and investigate the research challenges involved in realizing the proposed framework.

Tutorial: implementing a pedestrian tracker using inertial sensors

Shoe-mounted inertial sensors offer a convenient way to track pedestrians in situations where other localization systems fail. This tutorial outlines a simple yet effective approach for implementing a reasonably accurate tracker. This Web extra presents the Matlab implementation and a few sample recordings for implementing the pedestrian inertial tracking system using an error-state Kalman filter for zero-velocity updates (ZUPTs) and orientation estimation.

Utiliza����o de modelos virtuais tridimensionais na intera����o com a informa����o georreferenciada

Esta pesquisa tem como finalidade explorar os recursos de intera����o do usu��rio com a informa����o georreferenciada, utilizando o pr��prio ambiente f��sico e seus elementos como interface. A indexa����o geogr��fica de arquivos digitais e os recursos dispon��veis pela computa����o m��vel estabeleceram um novo modelo de intera����o com a informa����o. Cabe ao designer criar sistemas e interfaces que levem em considera����o a localiza����o do usu��rio no acesso da informa����o atribu��da ao entorno. Foi identificado que as solu����es desenvolvidas para esse prop��sito utilizam telas e outros aparatos tecnol��gicos que constrangem a rela����o do usu��rio com o ambiente e interferem na experi��ncia interativa. Como desdobramento da pesquisa foi desenvolvido um aplicativo que dispensa a tela na visualiza����o e intera����o com a camada informacional do ambiente f��sico. O sistema utiliza os sensores de localiza����o e orienta����o presentes nos smartphones para interagir com o entorno mapeado e georreferenciado. Dessa forma, o usu��rio, ao apontar o aparelho e selecionar diretamente o objeto de interesse, recebe os dados atribu��dos a ele. Sem a interfer��ncia de telas ou dispositivos imersivos, o pr��prio ambiente se apresenta como interface de intera����o, dispensando novos ��cones ou s��mbolos e tornando a tecnologia mais sutil em seu uso cotidiano.

Computer Vision and Pattern Recognition Technologies for Construction

This book will be of particular interest to academics, researchers, and graduate students at universities and industrial practitioners seeking to apply mobile and pervasive computing systems to improve construction industry productivity.

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