Browsing by Subject "real-time systems"

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    CORBA-JS: An Open-Standards Framework for Distributed Object Computing over the Web
    (Office of the Vice Chancellor for Research, 2013-04-05) Parulekar, Tejal B.; Feiock, Dennis C.; Hill, James H.
    Distributed object computing (DOC) is a well-established software engineering paradigm for implementing distributed real-time and embedded (DRE) systems, such as real-time monitoring systems. Likewise, CORBA is a well-established DOC open-standard used in DRE systems. Due to many technological limitations, DOC was traditionally unavailable in Web-based applications (i.e., stateful applications that communicate over HTTP, and are accessible via a Web browser) without the use of proprietary, custom technologies. The problem with using proprietary, custom technology is it creates fragmentation in the solution space where some solutions are not available to all end-users (e.g., Web sites that only work within a certain Web browser because of the used technology). With the advent of HTML5 and WebSockets, which is an open-standard for enabling two-way communication over HTTP, DOC now has the necessary technological foundations to be realized within Web applications without the use of proprietary, custom technologies. To date, however, no researchers have attempted to apply DOC over HTTP using well-established DOC open-standards, such as CORBA. This research therefore is an initial investigation into implementing CORBA atop of HTML5 and WebSockets. As part of this research, we are investigating the challenges in realizing the solution, and proposing ways to improve the target programming languages and CORBA specification. Doing so will enable developers to create feature-rich real-time Web applications that improve upon current state-of-the-art approaches, e.g., Asynchronous XML and JavaScript (AJAX), that are resource intensive (e.g., use a lot of CPU, network bandwidth, and memory) and hard to program.
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    Pedestrian Protection Using the Integration of V2V and the Pedestrian Automatic Emergency Braking System
    (IEEE, 2016-11) Tang, Bo; Chien, Stanley; Huang, Zhi; Chen, Yaobin; Department of Electrical and Computer Engineering, School of Engineering and Technology
    Vehicle to Vehicle (V2V) communication systems enable vehicles to communicate with each other and use the shared information to make safety related decisions. However, the safety improvement of the current V2V systems only benefits V2V-enabled objects in the V2V network. The Pedestrian Automatic Emergency Braking System (PAEB) can utilize onboard sensors to detect pedestrians and make safety related actions so it benefits the individual vehicle and the pedestrians detected by its PAEB. To further improve pedestrian safety, the idea for integrating the capabilities of V2V and PAEB (V2V-PAEB) has been proposed, which allows the information of pedestrians detected by onboard sensors of a vehicle to be shared in the V2V network. A V2V-PAEB enabled vehicle uses not only its onboard sensors, but also received V2V messages from others to detect potential collisions with pedestrians and make better safety related decisions. In this paper, a Matlab/Simulink based simulation model of V2V-PAEB system is presented for demonstrating the proper architecture and information processing processes, and for providing the quick start of developing a better simulation model of V2V-PAEB. The proposed model has also been tested in PreScan simulation environment.
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    SubTrack: Enabling Real-Time Tracking of Subway Riding on Mobile Devices
    (IEEE, 2017-11) Liu, Guo; Liu, Jian; Li, Fangmin; Ma, Xiaolin; Chen, Yingying; Liu, Hongbo; Computer and Information Science, School of Science
    Real-time tracking of subway riding will provide great convenience to millions of commuters in metropolitan areas. Traditional approaches using timetables need continuous attentions from the subway riders and are limited to the poor accuracy of estimating the travel time. Recent approaches using mobile devices rely on GSM and WiFi, which are not always available underground. In this work, we present SubTrack, utilizing sensors on mobile devices to provide automatic tracking of subway riding in real time. The real-time automatic tracking covers three major aspects of a passenger: detection of entering a station, tracking the passenger's position, and estimating the arrival time of subway stops. In particular, SubTrack employs the cell ID to first detect a passenger entering a station and exploits inertial sensors on the passenger's mobile device to track the train ride. Our algorithm takes the advantages of the unique vibrations in acceleration and typical moving patterns of the train to estimate the train's velocity and the corresponding position, and further predict the arrival time in real time. Our extensive experiments in two cities in China and USA respectively demonstrate that our system can accurately track the position of subway riders, predict the arrival time and push the arrival notification in a timely manner.