The building plants represent one of the main sources of power consumption and of greenhouse gases emission in urban scenarios. The efficiency of energy management is also related to the indoor environmental conditions that reflect on the user comfort. The constant monitoring of comfort indicators enables the accurate management of building plants with the final objective of reducing energy waste and satisfying the user needs. This paper presents an inversion methodology based on support vector regression for the reconstruction and forecasting of the thermal comfort of users starting from the indoor environmental features of the building. The environmental monitoring is performed by means of a wireless sensor network, which pervasively measures the spatial variability of indoor conditions. The proposed system has been experimentally validated in a real test-site to assess the advantages and the limitations in supporting the management of the building plants towards energy saving.
An inversion strategy for energy saving in smart building through wireless monitoring / Anselmi, N.; Moriyama, T.. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - STAMPA. - 904:(2017), pp. 0120031-0120036. [10.1088/1742-6596/904/1/012003]
An inversion strategy for energy saving in smart building through wireless monitoring
Anselmi, N.;
2017-01-01
Abstract
The building plants represent one of the main sources of power consumption and of greenhouse gases emission in urban scenarios. The efficiency of energy management is also related to the indoor environmental conditions that reflect on the user comfort. The constant monitoring of comfort indicators enables the accurate management of building plants with the final objective of reducing energy waste and satisfying the user needs. This paper presents an inversion methodology based on support vector regression for the reconstruction and forecasting of the thermal comfort of users starting from the indoor environmental features of the building. The environmental monitoring is performed by means of a wireless sensor network, which pervasively measures the spatial variability of indoor conditions. The proposed system has been experimentally validated in a real test-site to assess the advantages and the limitations in supporting the management of the building plants towards energy saving.File | Dimensione | Formato | |
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