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dc.contributorBecker, Eric Williamen_US
dc.date.accessioned2010-11-01T21:28:56Z
dc.date.accessioned2011-08-24T21:44:00Z
dc.date.available2010-11-01T21:28:56Z
dc.date.available2011-08-24T21:44:00Z
dc.date.issued2010-11-01
dc.date.submittedJanuary 2010en_US
dc.identifier.urihttp://hdl.handle.net/10106/5141
dc.description.abstractAs the population ages and technology advances, a need exists for creating ambient intelligent systems to be placed within the home environment. Attitudes towards technology have been changing, and home monitoring is now considered a less expensive and desirable alternative. Ideally, such systems should be small, wireless, and take the minimum of effort and cost to install and place within the home. In order to detect human activity in an assistive environment, key questions about the construction and operation of the technology and methods needed to detect that activity. To that end, a computational framework has been created inside an apartment testbed combining a variety of algorithms, tools, and methods that support an assistive living apartment using Wireless Sensor Networks and other devices and sensorsen_US
dc.language.isoenen_US
dc.publisherComputer Science & Engineeringen_US
dc.titleEvent Recognition From Ambient Assistive Living Technologiesen_US
dc.typePh.D.en_US


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