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Full-Text Articles in VLSI and Circuits, Embedded and Hardware Systems

Contextualized Mobile Support For Learning By Doing In The Real World, Ray Bareiss, Natalie Linnell, Martin L. Griss Sep 2012

Contextualized Mobile Support For Learning By Doing In The Real World, Ray Bareiss, Natalie Linnell, Martin L. Griss

Martin L Griss

This research addresses the use of mobile devices with both embedded and external sensors to provide contextualized help, advice, and remediation to learners engaged in real-world learn-by-doing tasks. This work is situated within the context of learning a complex procedure, in particular emergency responders learning to conduct urban search and rescue operations. Research issues include the design and delivery of contextualized performance support and the inferring of learner actions and intentions from sensor data to ensure that the right support is delivered just in time, as it is relevant to what the learner is doing.


Semantic Geotagging: A Location-Based Hypermedia Approach To Creating Situational Awareness, Ray Bareiss, Martin Griss, Steven Rosenberg, Yu Zhang Sep 2011

Semantic Geotagging: A Location-Based Hypermedia Approach To Creating Situational Awareness, Ray Bareiss, Martin Griss, Steven Rosenberg, Yu Zhang

Martin L Griss

As emergency first responders and commanders increasingly use mobile phones, tablets, and social media to communicate, coordinate, and manage information during disasters, we see a need and opportunity to provide a mobile device-appropriate semantic layer to a geographically-based common operating picture. The challenge is to provide a simple, usable structure for a rapidly growing body of information to simplify the development of situational awareness in an unfolding disaster. We use a hyperlinked structure based on the ASK model to organize information in a readily accessible form. In this paper we describe our initial design and experience with an Android-based prototype, …


Leveraging Mobile Context For Effective Collaboration And Task Management In Disaster Response, Faisal Luqman, Martin L. Griss Mar 2011

Leveraging Mobile Context For Effective Collaboration And Task Management In Disaster Response, Faisal Luqman, Martin L. Griss

Martin L Griss

Collaboration and task management is challenging in distributed, dynamically-formed teams, typical in large scale disaster response scenarios. Ineffective collaboration may result in poor performance and possible loss of life. In this paper, we present Overseer, an agent-based system that exploits context information from mobile devices to facilitate collaboration and task allocation. We describe our system architecture and show how mobile context can be used to create dynamic role-based assignments to support collaboration and effective task management.


Anubis: An Attestation Protocol For Distributed Context-Aware Applications, Senaka Buthpitiya, Feng-Tso Sun, Heng-Tze Chen, Patrick Tague, Martin L. Griss, Anind K. Dey Jan 2011

Anubis: An Attestation Protocol For Distributed Context-Aware Applications, Senaka Buthpitiya, Feng-Tso Sun, Heng-Tze Chen, Patrick Tague, Martin L. Griss, Anind K. Dey

Martin L Griss

Sharing sensitive context information among multiple distributed components in mobile environments introduces major security concerns. The distributed sensing, processing and actuating components of these applications can be compromised and modified or impersonated to extract private and confidential information or to inject false information. In this paper we present the Anubis protocol for remote code attestation and access control of distributed components using remote execution of trusted code. Our Anubis protocol leverages previous work in the fields of wireless sensor networks and secure web browsing. Anubis allows new components to be introduced to the environment without updating existing components. Our implementation …


Mobile Context-Aware Personal Messaging Assistant, Senaka Buthpitiya, Deepthi Madamanchi, Sumalatha Kommaraju, Martin L. Griss Jan 2011

Mobile Context-Aware Personal Messaging Assistant, Senaka Buthpitiya, Deepthi Madamanchi, Sumalatha Kommaraju, Martin L. Griss

Martin L Griss

A previous study shows that busy professionals receive in excess of 50 emails per day of which approximately 23% require immediate attention, 13% require attention later and 64% are unimportant and typically ignored. The flood of emails impact mobile users even more heavily. Flooded inboxes cause busy professionals to spend considerable amounts of time searching for important messages, and there has been much research into automating the process using email content for classification; but we find email priority depends also on user context. In this paper we describe the Personal Messaging Assistant (PMA), an advanced rule-based email management system which …


Sensorchestra: Collaborative Sensing For Symbolic Location Recognition, Heng-Tze Cheng, Feng-Tso Sun, Senaka Buthpitiya, Martin L. Griss Jan 2011

Sensorchestra: Collaborative Sensing For Symbolic Location Recognition, Heng-Tze Cheng, Feng-Tso Sun, Senaka Buthpitiya, Martin L. Griss

Martin L Griss

"Symbolic location of a user, like a store name in a mall, is essential for context-based mobile advertising. Existing fingerprint- based localization using only a single phone is susceptible to noise, and has a major limitation in that the phone has to be held in the hand at all times. In this paper, we present SensOrchestra, a col- laborative sensing framework for symbolic location recognition that groups nearby phones to recognize ambient sounds and images of a location collaboratively. We investigated audio and image features, and designed a classifier fusion model to integrate estimates from diff erent phones. We also …


Activity-Aware Mental Stress Detection Using Physiological Sensors, Feng-Tso Sun, Cynthia Kuo, Heng-Tze Cheng, Senaka Buthpitiya, Patricia Collins, Martin Griss Jan 2011

Activity-Aware Mental Stress Detection Using Physiological Sensors, Feng-Tso Sun, Cynthia Kuo, Heng-Tze Cheng, Senaka Buthpitiya, Patricia Collins, Martin Griss

Martin L Griss

"Continuous stress monitoring may help users better understand their stress patterns and provide physicians with more reliable data for interventions. Previously, studies on mental stress detection were limited to a laboratory environment where participants generally rested in a sedentary position. However, it is impractical to exclude the effects of physical activity while developing a pervasive stress monitoring application for everyday use. The physiological responses caused by mental stress can be masked by variations due to physical activity. We present an activity-aware mental stress detection scheme. Electrocardiogram (ECG), galvanic skin response (GSR), and accelerometer data were gathered from 20 participants across …


Omnisense: A Collaborative Sensing Framework For User Context Recognition Using Mobile Phones, Heng-Tze Cheng, Senaka Buthpitiya, Feng-Tso Sun, Martin L. Griss Jan 2011

Omnisense: A Collaborative Sensing Framework For User Context Recognition Using Mobile Phones, Heng-Tze Cheng, Senaka Buthpitiya, Feng-Tso Sun, Martin L. Griss

Martin L Griss

Context information, including a user’s locations and activities, is indispensable for context-aware applications such as targeted advertising and disaster response. Inferring user context from sensor data is intrinsically challenging due to the semantic gap between low-level signals and high-level human activities. When implemented on mobile phones, more challenges on resource limitations are present. While most existing work focuses on context recognition using a single mobile phone, collaboration among multiple phones has received little attention, and the recognition accuracy is susceptible to phone position and ambient changes. Simply putting a phone in one’s pocket can render the microphone muffled and the …


Room-Level Wi-Fi Location Tracking, Joshua Correa, Ed Katz, Patricia Collins, Martin Griss Jan 2011

Room-Level Wi-Fi Location Tracking, Joshua Correa, Ed Katz, Patricia Collins, Martin Griss

Martin L Griss

Context-aware applications for indoor intelligent environments require an appropriately accurate and stable interior positioning system to adapt services to the location of a mobile user or mobile device in a building. Different technologies provide a varying mix of resolution, accuracy, stability and challenges. In this paper we report on our experience using an existing Wi-Fi infrastructure without specialized hardware added to support location tracking. There are several approaches to track the location of Wi-Fi enabled devices within a building such as signal propagation models and signature matching. We found signature matching most effective in our environment. Signature matching is accomplished …