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Pre- and Post-Self-Renovation Variations in Indoor Temperature: Methodological Pipeline and Cloud Monitoring Results in Two Small Residential Buildings

Author

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  • Giacomo Chiesa

    (Department of Architecture and Design, Politecnico di Torino, 10125 Turin, Italy)

  • Paolo Carrisi

    (Department of Architecture and Design, Politecnico di Torino, 10125 Turin, Italy)

Abstract

The impacts of renovation actions on pre- and post-retrofitting building performances are complex to analyse, particularly small and potentially self-actuated actions, such as adding insulation layers to a cold roof slab or changing doors. These interventions are widespread in small residential houses and cases where the owners are the residents. However, a large research gap currently remains regarding the impact of sustainable solutions on building performance. This study aims to address this issue by proposing a methodology based on commercial cloud monitoring solutions and middleware development that analyses and reports on the impact of such solutions to end users, allowing for an analysis of real variations in air temperature levels. The methodology is applied to two single/double-family residential houses, acting as demo cases for verification, across a multi-year time horizon. In both cases, measurements were conducted before and after typical limited renovation actions. Alongside the proposed methodology, descriptions of the smart solutions’ requirements are provided. The results mainly focus on temperature variations. Finally, the impact of the solutions on energy consumption was analysed for one of the buildings, and feedback was briefly provided by the users.

Suggested Citation

  • Giacomo Chiesa & Paolo Carrisi, 2025. "Pre- and Post-Self-Renovation Variations in Indoor Temperature: Methodological Pipeline and Cloud Monitoring Results in Two Small Residential Buildings," Energies, MDPI, vol. 18(15), pages 1-28, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:15:p:3928-:d:1708135
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    References listed on IDEAS

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    1. Giacomo Chiesa & Francesca Fasano & Paolo Grasso, 2021. "A New Tool for Building Energy Optimization: First Round of Successful Dynamic Model Simulations," Energies, MDPI, vol. 14(19), pages 1-20, October.
    2. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
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    4. Cozza, Stefano & Chambers, Jonathan & Patel, Martin K., 2020. "Measuring the thermal energy performance gap of labelled residential buildings in Switzerland," Energy Policy, Elsevier, vol. 137(C).
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