2017
DOI: 10.1007/978-3-319-65636-6_46
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Energy Optimization Techniques for Demand-Side Management in Smart Homes

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Cited by 5 publications
(7 citation statements)
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“…The list of activities of interest is detailed in [24] and includes activities such as cooking and sleeping. By correctly identifying activities, it is possible to decide when to interact with the user in a smart setting [1], provide custom care such as nursing for the elderly [27], or help users who suffer from mild impairment [30]. Inferring activities done by the user is an interesting problem typically addressed through either data-based or knowledge-based methods [9].…”
Section: Adlmentioning
confidence: 99%
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“…The list of activities of interest is detailed in [24] and includes activities such as cooking and sleeping. By correctly identifying activities, it is possible to decide when to interact with the user in a smart setting [1], provide custom care such as nursing for the elderly [27], or help users who suffer from mild impairment [30]. Inferring activities done by the user is an interesting problem typically addressed through either data-based or knowledge-based methods [9].…”
Section: Adlmentioning
confidence: 99%
“…For example the specifications actfloor(0) and actfloor(1) require the verdicts from monitors associated with cooking and sleeping, respectively, since cooking happens on the ground floor while sleeping on the first floor. Furthermore, we can disjoin actfloor(0) and actfloor(1) to easily specify that an activity has happened in the house, acthouse def = actfloor(0) ∨ actfloor (1). While specification acthouse can be seen as a quantified version of actfloor(i), we can use modular specifications for behavior, for example we can verify the triggering of an alarm in the house within 5 timestamps of detecting a fire hazard, i.e.…”
Section: Advantages Of Decentralized Specificationsmentioning
confidence: 99%
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“…The list of activities of interest is detailed in [33] and includes activities such as cooking and sleeping. By correctly identifying activities, it is possible to decide when to interact with the user in a smart setting [1], provide custom care such as nursing for the elderly [37], or help users who suffer from mild impairment [42]. Inferring activities done by the user is an interesting problem typically addressed through either data-based or knowledge-based methods [13].…”
Section: Adlmentioning
confidence: 99%
“…Overall, we see our contributions as follows 1 : -We apply decentralized RV to analyze traces of over 36,000 timestamps spanning 27 sensors in a real smart apartment (Sect. 1.1).…”
mentioning
confidence: 99%