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Research associate, Simon Fraser University (2008-09) Webpage SFU Research associate, UVA (2005-07) Department of Computer
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RESEARCH INTERESTS
My research activity lies in sensor networks (wireless or wired), electronics, human behavior modeling, ubiquitous and pervasive computing, context awareness, circadian activity rhythms (CARs) for home automation, smart homes, and ambient assisted living. Much of my research is devoted to elaborate prototypes based on sensor networks that are capable of embedding innovative designs, functionalities, and modeling techniques.
I have also created the concept of "circadian activity rhythms" (CARs) in the context of health information systems to assess the human behavior using a predictive and dedicated model. CARs presuppose that the human behavior follows a daily life rhythm of 24 hours (circadian), which we can measure through continuous passive monitoring of the physical activity engaged in a habitat (or outside by extension). CARs are influenced by social or biological rhythms as well as other factors such as the places of residence, the seasons, etc. Within ambient intelligent systems, CARs can have multiple applications such as context-aware wireless sensor networks in the AlarmNet project.
Selected publications
A. Wood, G. Virone, T. Doan, Q. Cao, L. Selavo, Y. Wu, L. Fang, Z. He, S. Lin, and J. Stankovic, “AlarmNet: Wireless Sensor Networks for Assisted-Living And Residential Monitoring,” technical report CS-2006-11, Department of Computer Science, University of Virginia, 2006
Abstract: We describe ALARMNET, a wireless sensor network for assisted-living and residential monitoring. It integrates environmental and physiological sensors in a scalable, heterogeneous architecture. A query protocol allows real-time collection and processing of sensor data by user interfaces and back-end analysis programs. One such program determines circadian activity rhythms of residents, feeding activity information back into the sensor network to aid context-aware power management, dynamic privacy policies, and data association. Communication is secured end-to-end to protect sensitive medical and operational information. The ALARMNET system has been implemented as a network of MICAz sensors, stargate gateways, iPAQ PDAs, and PCs. Customized infrared motion and dust sensors, and integrated temperature, light, pulse, and blood oxygenation sensors are present. Software components include: TinyOS query processor and security modules for motes; AlarmGate, an embedded Java application for managing power, privacy, security, queries, and client connections; Java resident monitoring and sensor data querying applications for PDAs and PCs; and a circadian activity rhythm analysis program. We show the correctness, robustness, and extensibility of the system architecture through a scenario-based evaluation of the integrated ALARM-NET system, as well as performance data for individual software components.
G. Virone, A. Wood, L. Selavo, Q. Cao, L. Fang, T. Doan, Z. He, R. Stoleru, S. Lin, and J.A. Stankovic, “An Assisted Living Oriented Information System Based on a Residential Wireless Sensor Network,” Proceedings of the 1st Distributed Diagnosis and Home Healthcare (D2H2) Conference, Arlington, Virginia, USA, pp. 95-100, April 2-4, 2006
Abstract: This paper deals with a new medical information system called AlarmNet designed for smart healthcare. Based on an advanced Wireless Sensor Network (WSN), it specifically targets assisted-living residents and others who may benefit from continuous and remote health monitoring. We present the advantages, objectives, and status of the system built at the Department of Computer Science at UVA. Early results of the prototype suggest a strong potential for WSNs to open new research perspectives for ad hoc deployment of multi-modal sensors and improved quality of medical care.
- Industrial Computer Science (45.5 hours of practical courses), undergraduate classes at Grenoble IUT1.
- Electronics (38.5 hours of practical courses).
- Microprocessors (48 hours of full course: lecture, exercices and practice).
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All content, images © G.Virone
Last modified: 07/05/2008
