Context-aware information systems count on sensors for establishing the user situation and adjusting their behavior accordingly. Nevertheless, there are quite some situations where sensors would be insufficiently effe...
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ISBN:
(纸本)9783031367564;9783031367571
Context-aware information systems count on sensors for establishing the user situation and adjusting their behavior accordingly. Nevertheless, there are quite some situations where sensors would be insufficiently effective: (a) Sometimes it is physically challenging to mount sensors at the optimal position, resulting in lower quality of the gathered data;(b) Mental aspects, such as user intentions, emotions, arousal, motivation, and engagement, are not easy to capture by means of sensors;(c) Data fusion concerning data from different sensors could result in wrong inferences. We propose combining / augmenting sensor-based approaches with data analytics that can make predictions about larger groups of users. When the focal user is a member of that larger group and when there are more users with a similar profile, predictions about the focal user can be made. We combine context awareness conceptualizations and relevant data analysis techniques, and we reflect on these choices in a discussion concerning the usefulness of applying data analytics in facilitating context-aware computing. The paper illustrates the concepts with an example from the transport domain.
As recent optoelectronic devices evolve beyond passive light sensors, their photoinduced memory effects are offering new possibilities for sensor-based artificial intelligence through the integration of sensing and co...
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As recent optoelectronic devices evolve beyond passive light sensors, their photoinduced memory effects are offering new possibilities for sensor-based artificial intelligence through the integration of sensing and computation. These applications have been developed utilizing a broad range of photoresponse times;however, a comprehensive, unified perspective for categorizing these mechanisms based on response time remains elusive. By encompassing the fast-decaying responses in photodetectors and the persistent memory states in optoelectronic synapses, this perspective provides a systematic framework for understanding the broad spectrum of photoresponse time scales associated with photoinduced memory effects in optoelectronic devices. We first introduce the mechanisms of photocurrent generation through photoconductive and photogating effects, and then we provide an overview of photoresponse times, both with and without consideration of recombination time, covering volatile and nonvolatile processes. Finally, we highlight the role of photoinduced memory effects in various emerging intelligent sensor technologies.
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