Computer Engineering Commons^™

Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann M. Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito

Ole J Mengshoel

Mobile Computing: Challenges And Opportunities For Autonomy And Feedback, Ole J. Mengshoel, Bob Iannucci, Abe Ishihara

Ole J Mengshoel

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.

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.

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

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 …

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

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 …

Towards New Web Services Based Supervisory Systems Dedicated To Nomadic Operators, Djilali Idoughi, Christophe Kolski

Professor Djilali IDOUGHI

This paper outlines new approaches and motivations about supervisory HMI, such as mobility and information access by different human actors belonging to the organization, by using diverse interaction devices, exploiting Web Services and their underlying technologies. The basic concepts are explained in the context of industrial supervision adopting a service oriented architecture (SOA) design approach which makes it possible to integrate real time information from different systems more easily than traditional ones. A representative supervisory scenario which illustrates the approach is described and discussed.