The impact of electricity consumption in buildings on the overall energy budget of European and North-American states is steadily growing and requires solutions for achieving a more sustainable development. Smart metering and energy management system can be hardly afforded by residential homes, for their cost and the required granularity. Empowering smart homes with suitable power consumption models allows to estimate, in real-time, the current home consumption on the basis of currently active devices. In this paper we introduce an ontology based power consumption model (PowerOnt) for smart homes, and we discuss some application use cases where the proposed approach may successfully be exploited. Results show that the modeling approach has the potential to support energy efficiency measures into residential homes with few or no metering devices.

PowerOnt: An Ontology-based Approach for Power Consumption Estimation in Smart Homes / Bonino, Dario; Corno, Fulvio; DE RUSSIS, Luigi. - STAMPA. - 150:(2015), pp. 3-8. (Intervento presentato al convegno The First International Conference on Cognitive Internet of Things Technologies tenutosi a Roma, Italy nel 27 October 2014) [10.1007/978-3-319-19656-5_1].

PowerOnt: An Ontology-based Approach for Power Consumption Estimation in Smart Homes

BONINO, DARIO;CORNO, Fulvio;DE RUSSIS, LUIGI
2015

Abstract

The impact of electricity consumption in buildings on the overall energy budget of European and North-American states is steadily growing and requires solutions for achieving a more sustainable development. Smart metering and energy management system can be hardly afforded by residential homes, for their cost and the required granularity. Empowering smart homes with suitable power consumption models allows to estimate, in real-time, the current home consumption on the basis of currently active devices. In this paper we introduce an ontology based power consumption model (PowerOnt) for smart homes, and we discuss some application use cases where the proposed approach may successfully be exploited. Results show that the modeling approach has the potential to support energy efficiency measures into residential homes with few or no metering devices.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2570936
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