Titlebook: Ambient Intelligence; European Conference, Emile Aarts,Boris de Ruyter,Gregory O‘Hare Conference proceedings 2014 Springer International Pu

倔強(qiáng)一點(diǎn)

aspersion

Medicaid

Learning and Recognizing Routines and Activities in SOFiA, is doing. To this aim we developed a system called WoMan that, using a process mining approach, is able to incrementally learn user’s activities and daily routines as workflow models. In order to test its efficacy in a real-world setting, we set up a smart office environment, SOFiA, equipped with a

ALOFT

On-line Context Aware Physical Activity Recognition from the Accelerometer and Audio Sensors of Smauser (health monitoring, fitness, context-awareness) as well as for third party applications and social network (performance sharing, profiling). Most of the research effort has been focused on direct recognition from accelerometer sensors and few studies have integrated the audio channel in their m

Nonthreatening

accrete

Developing a Face Monitoring Robot for a Desk Worker,ect to search for the desk worker and adjusts its position for monitoring. The monitoring is based on incremental clustering of the faces. Our experiments revealed that not only Animation Units (AUs) features, which represent deviations from the neutral face, but also the pitch angle of the face nor

無情

discord

Ambient Intelligence978-3-319-14112-1Series ISSN 0302-9743 Series E-ISSN 1611-3349

慢慢啃

https://doi.org/10.1007/978-3-642-94141-2ts and the Internet of Things, showing how it can be used to effect discrete control in smart home environments by mediating and adapting generic rules through finite-state-machine models drawn from a domain ontology, representing observable & controllable “things” and space entities in this infrastructure.

一再困擾

Acta Neurochirurgica Supplementtems for the elderly and energy consumption optimization. Sensing the environmental state via different sensors is the first and crucial component of every ambient intelligent system. In this work we investigate the use of environmental sounds for touch-free audio-based device recognition in a home