| id |
caadria2018_046 |
| authors |
Lu, Siliang and Cochran Hameen, Erica |
| year |
2018 |
| title |
Integrated IR Vision Sensor for Online Clothing Insulation Measurement |
| source |
T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 565-573 |
| doi |
https://doi.org/10.52842/conf.caadria.2018.1.565
|
| summary |
As one of the most important building systems, HVAC plays a key role in creating a comfortable thermal environment. Predicted Mean Vote (PMV), an index that predicts the mean value of the votes of a large group of persons on the thermal sensation scale, has been adopted to evaluate the built environment. Compared to environmental factors, clothing insulation can be much harder to measure in the field. The existing research on real-time clothing insulation measurement mainly focuses on expensive infrared thermography (IR) cameras. Therefore, to ensure cost-effectiveness, the paper has proposed a solution consisting of a normal camera, IR and air temperature sensors and Arduino Nanos to measure clothing insulation in real-time. Moreover, the algorithm includes the initialization from clothing classification with pre-trained neural network and optimization of the clothing insulation calculation. A total of 8 tests have been conducted with garments for spring/fall, summer and winter. The current results have shown the accuracy of T-shirt classification can reach over 90%. Moreover, compared with the results with IR cameras and reference values, the accuracies of the proposed sensing system vary with different clothing types. Research shall be further conducted and be applied into the dynamic PMV-based HVAC control system. |
| keywords |
clothing insulation; skin temperature; clothing classification; IR temperature sensor; Optimization |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (1,882,245 bytes) |
| last changed |
2022/06/07 07:59 |
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