Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated Analysis
The application of building retrofitting solutions targeting improved energy efficiency and thermal comfort is significantly influenced by environmental and climate conditions. This study aims to automate a reliable dataset and enhance the predictability of the post-retrofit performance of the build...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/15/7/1050 |
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| author | Elena Imani Huda Dawood Sean Williams Nashwan Dawood |
| author_facet | Elena Imani Huda Dawood Sean Williams Nashwan Dawood |
| author_sort | Elena Imani |
| collection | DOAJ |
| description | The application of building retrofitting solutions targeting improved energy efficiency and thermal comfort is significantly influenced by environmental and climate conditions. This study aims to automate a reliable dataset and enhance the predictability of the post-retrofit performance of the buildings. The proposed hybrid methodology utilises physics-based and data-driven methods to evaluate a range of retrofitting scenarios across diverse UK climate zones and validates an automated dataset with real-time data collected via IoT (Internet of things)-based sensors. This hybrid method enables a comprehensive assessment of retrofitting solutions’ impacts on building performance. The collected data create a reliable dataset and serve as the foundation for training machine learning (ML) prediction models and support decisions in retrofit strategies. The findings reveal that in cool–humid climates, the air source heat pumps significantly perform better when compared to 58 heating systems in terms of the balance of energy efficiency and thermal comfort. Moreover, Water Source Heat Pumps (WSHPs) are recommended for colder regions. As a result, zone-specific retrofitting strategies with seasonal adjustments are recommended for achieving optimum energy efficiency and thermal comfort. |
| format | Article |
| id | doaj-art-b59909d1491e4311ba5d4be4eccf9db9 |
| institution | OA Journals |
| issn | 2075-5309 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj-art-b59909d1491e4311ba5d4be4eccf9db92025-08-20T02:09:15ZengMDPI AGBuildings2075-53092025-03-01157105010.3390/buildings15071050Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated AnalysisElena Imani0Huda Dawood1Sean Williams2Nashwan Dawood3School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UKSchool of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UKNet Zero Industry Innovation Centre (NZIIC), Teesside University, Middlesbrough TS2 1DJ, UKNet Zero Industry Innovation Centre (NZIIC), Teesside University, Middlesbrough TS2 1DJ, UKThe application of building retrofitting solutions targeting improved energy efficiency and thermal comfort is significantly influenced by environmental and climate conditions. This study aims to automate a reliable dataset and enhance the predictability of the post-retrofit performance of the buildings. The proposed hybrid methodology utilises physics-based and data-driven methods to evaluate a range of retrofitting scenarios across diverse UK climate zones and validates an automated dataset with real-time data collected via IoT (Internet of things)-based sensors. This hybrid method enables a comprehensive assessment of retrofitting solutions’ impacts on building performance. The collected data create a reliable dataset and serve as the foundation for training machine learning (ML) prediction models and support decisions in retrofit strategies. The findings reveal that in cool–humid climates, the air source heat pumps significantly perform better when compared to 58 heating systems in terms of the balance of energy efficiency and thermal comfort. Moreover, Water Source Heat Pumps (WSHPs) are recommended for colder regions. As a result, zone-specific retrofitting strategies with seasonal adjustments are recommended for achieving optimum energy efficiency and thermal comfort.https://www.mdpi.com/2075-5309/15/7/1050energy efficiencythermal comfortbuilding retrofittingphysics-based simulationdata-driven analysisIoT-based validation |
| spellingShingle | Elena Imani Huda Dawood Sean Williams Nashwan Dawood Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated Analysis Buildings energy efficiency thermal comfort building retrofitting physics-based simulation data-driven analysis IoT-based validation |
| title | Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated Analysis |
| title_full | Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated Analysis |
| title_fullStr | Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated Analysis |
| title_full_unstemmed | Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated Analysis |
| title_short | Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated Analysis |
| title_sort | physics based and data driven retrofitting solutions for energy efficiency and thermal comfort in the uk iot validated analysis |
| topic | energy efficiency thermal comfort building retrofitting physics-based simulation data-driven analysis IoT-based validation |
| url | https://www.mdpi.com/2075-5309/15/7/1050 |
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