Measuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensors
Abstract Measuring and controlling human thermal perception-related parameters within the built environment is crucial for ensuring occupant comfort, productivity, well-being, and reduced energy consumption. The human body is sensitive to both convective and radiative thermal effects. Mean radiant t...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-55122-z |
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| _version_ | 1832571547867414528 |
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| author | Fatih Evren Sayan Biswas Richard Graves |
| author_facet | Fatih Evren Sayan Biswas Richard Graves |
| author_sort | Fatih Evren |
| collection | DOAJ |
| description | Abstract Measuring and controlling human thermal perception-related parameters within the built environment is crucial for ensuring occupant comfort, productivity, well-being, and reduced energy consumption. The human body is sensitive to both convective and radiative thermal effects. Mean radiant temperature represents the comprehensive radiant thermal impact individuals perceive in their surroundings. However, no feasible, robust, and ergonomic methods exist for real-time mean radiant temperature measurements in the built environment. In this paper, we introduce a method for measuring longwave mean radiant temperature utilizing low-resolution infrared temperature sensors. The approach utilizes projective transformations to derive surface temperature distributions from raw infrared thermal data. Our technique is tested in four diverse real-world environments, encompassing different heating methods and room configurations, resulting in a maximum error of ±0.5 °C. The results demonstrate the method’s repeatability and robustness across diverse room sizes, layouts, and scenarios, suggesting its potential integration into room thermostats to improve human comfort while optimizing building energy utilization. We anticipate that this method will revolutionize sensing in the built environment by eliminating the requirement for costly hardware. |
| format | Article |
| id | doaj-art-d794e24191db481cb678e112dcd5cc9d |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-d794e24191db481cb678e112dcd5cc9d2025-02-02T12:31:50ZengNature PortfolioNature Communications2041-17232025-01-0116111010.1038/s41467-024-55122-zMeasuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensorsFatih Evren0Sayan Biswas1Richard Graves2Department of Mechanical Engineering, University of Minnesota Twin CitiesDepartment of Mechanical Engineering, University of Minnesota Twin CitiesCenter for Sustainable Building Research, University of Minnesota Twin CitiesAbstract Measuring and controlling human thermal perception-related parameters within the built environment is crucial for ensuring occupant comfort, productivity, well-being, and reduced energy consumption. The human body is sensitive to both convective and radiative thermal effects. Mean radiant temperature represents the comprehensive radiant thermal impact individuals perceive in their surroundings. However, no feasible, robust, and ergonomic methods exist for real-time mean radiant temperature measurements in the built environment. In this paper, we introduce a method for measuring longwave mean radiant temperature utilizing low-resolution infrared temperature sensors. The approach utilizes projective transformations to derive surface temperature distributions from raw infrared thermal data. Our technique is tested in four diverse real-world environments, encompassing different heating methods and room configurations, resulting in a maximum error of ±0.5 °C. The results demonstrate the method’s repeatability and robustness across diverse room sizes, layouts, and scenarios, suggesting its potential integration into room thermostats to improve human comfort while optimizing building energy utilization. We anticipate that this method will revolutionize sensing in the built environment by eliminating the requirement for costly hardware.https://doi.org/10.1038/s41467-024-55122-z |
| spellingShingle | Fatih Evren Sayan Biswas Richard Graves Measuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensors Nature Communications |
| title | Measuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensors |
| title_full | Measuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensors |
| title_fullStr | Measuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensors |
| title_full_unstemmed | Measuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensors |
| title_short | Measuring mean radiant temperature for indoor comfort assessment using low-resolution optical sensors |
| title_sort | measuring mean radiant temperature for indoor comfort assessment using low resolution optical sensors |
| url | https://doi.org/10.1038/s41467-024-55122-z |
| work_keys_str_mv | AT fatihevren measuringmeanradianttemperatureforindoorcomfortassessmentusinglowresolutionopticalsensors AT sayanbiswas measuringmeanradianttemperatureforindoorcomfortassessmentusinglowresolutionopticalsensors AT richardgraves measuringmeanradianttemperatureforindoorcomfortassessmentusinglowresolutionopticalsensors |