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Yang, Bin
Publications (10 of 80) Show all publications
Cheng, X., Yang, B., Tan, K., Isaksson, E., Hedman, A., Olofsson, T. & Li, H. (2019). A Contactless Measuring Method of Skin Temperature based on the Skin Sensitivity Index and Deep Learning. Applied Sciences: APPS, 9(7), Article ID 1375.
Open this publication in new window or tab >>A Contactless Measuring Method of Skin Temperature based on the Skin Sensitivity Index and Deep Learning
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2019 (English)In: Applied Sciences: APPS, ISSN 1454-5101, E-ISSN 1454-5101, Vol. 9, no 7, article id 1375Article in journal (Refereed) [Artistic work] Published
Abstract [en]

In human-centered intelligent building, real-time measurements of human thermal comfort play critical roles and supply feedback control signals for building heating, ventilation, and air conditioning (HVAC) systems. Due to the challenges of intra- and inter-individual differences and skin subtleness variations, there has not been any satisfactory solution for thermal comfort measurements until now. In this paper, a contactless measuring method based on a skin sensitivity index and deep learning (NISDL) was proposed to measure real-time skin temperature. A new evaluating index, named the skin sensitivity index (SSI), was defined to overcome individual differences and skin subtleness variations. To illustrate the effectiveness of SSI proposed, a two multi-layers deep learning framework (NISDL method I and II) was designed and the DenseNet201 was used for extracting features from skin images. The partly personal saturation temperature (NIPST) algorithm was use for algorithm comparisons. Another deep learning algorithm without SSI (DL) was also generated for algorithm comparisons. Finally, a total of 1.44 million image data was used for algorithm validation. The results show that 55.62% and 52.25% error values (NISDL method I, II) are scattered at (0 °C, 0.25 °C), and the same error intervals distribution of NIPST is 35.39%. 

Place, publisher, year, edition, pages
Switzerland: MDPI, 2019
Keywords
contactless measurements; skin sensitivity index; thermal comfort; subtleness magnification; deep learning; piecewise stationary time series
National Category
Civil Engineering
Identifiers
urn:nbn:se:umu:diva-159773 (URN)10.3390/app9071375 (DOI)
Available from: 2019-06-05 Created: 2019-06-05 Last updated: 2019-06-20Bibliographically approved
Ma, K., Yu, Y., Yang, B. & Yang, J. (2019). Demand-Side Energy Management Considering Price Oscillations for Residential Building Heating and Ventilation Systems. IEEE Transactions on Industrial Informatics
Open this publication in new window or tab >>Demand-Side Energy Management Considering Price Oscillations for Residential Building Heating and Ventilation Systems
2019 (English)In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050Article in journal (Refereed) Epub ahead of print
Abstract [en]

This paper presents an energy management method to optimally control the energy supply and the temperature settings of distributed heating and ventilation systems for residential buildings. The control model attempts to schedule the supply and demand simultaneously with the purpose of minimizing the total costs. Moreover, the Predicted Percentage of Dissatisfied (PPD) model is introduced into the consumers' cost functions and the quadratic fitting method is applied to simplify the PPD model. An energy management algorithm is developed to seek the optimal temperature settings, the energy supply and the price. Furthermore, due to the ubiquity of price oscillations in electricity markets, we analyze and examine the effects of price oscillations on the performance of the proposed algorithm. Finally, the theoretical analysis and simulation results both demonstrate that the proposed energy management algorithm with price oscillations can converge to a region around the optimal solution.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Energy management, Demand response (DR), Heating and ventilation, Price oscillations, Gradient algorithm
National Category
Building Technologies
Identifiers
urn:nbn:se:umu:diva-156934 (URN)10.1109/TII.2019.2901306 (DOI)
Available from: 2019-03-02 Created: 2019-03-02 Last updated: 2019-03-15
Cheng, X., Yang, B., Hedman, A., Olofsson, T., Li, H. & van Gool, L. (2019). NIDL: A pilot study of contactless measurement of skin temperature for intelligent building. Energy and Buildings, 198, 340-352
Open this publication in new window or tab >>NIDL: A pilot study of contactless measurement of skin temperature for intelligent building
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2019 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 198, p. 340-352Article in journal (Refereed) [Artistic work] Published
Abstract [en]

Human thermal comfort measurement plays a critical role in giving feedback signals for building energy efficiency. A contactless measuring method based on subtleness magnification and deep learning (NIDL) was designed to achieve a comfortable, energy efficient built environment. The method relies on skin feature data, e.g., subtle motion and texture variation, and a 315-layer deep neural network for constructing the relationship between skin features and skin temperature. A physiological experiment was conducted for collecting feature data (1.44 million) and algorithm validation. The contactless measurement algorithm based on a partly-personalized saturation temperature model (NIPST) was used for algorithm performance comparisons. The results show that the mean error and median error of the NIDL are 0.476 °C and 0.343°C which is equivalent to accuracy improvements of 39.07 % and 38.76 %, respectively.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Contactless method, Thermal comfort measurement, Vision-based subtleness magnification, Deep learning, Intelligent building
National Category
Civil Engineering
Identifiers
urn:nbn:se:umu:diva-159772 (URN)10.1016/j.enbuild.2019.06.007 (DOI)000477091800027 ()2-s2.0-85067305627 (Scopus ID)
Available from: 2019-06-05 Created: 2019-06-05 Last updated: 2019-09-06Bibliographically approved
Kabanshi, A., Yang, B., Sörqvist, P. & Sandberg, M. (2019). Occupants' perception of air movements and air quality in a simulated classroom with an intermittent air supply system. Indoor + Built Environment, 28(1), 63-76
Open this publication in new window or tab >>Occupants' perception of air movements and air quality in a simulated classroom with an intermittent air supply system
2019 (English)In: Indoor + Built Environment, ISSN 1420-326X, E-ISSN 1423-0070, Vol. 28, no 1, p. 63-76Article in journal, Editorial material (Refereed) Published
Abstract [en]

The study reported herein builds on occupant response to an intermittent air jet strategy (IAJS), which creates periodic airflow and non-isothermal conditions in the occupied zone. Previous research has highlighted benefits of IAJS for the thermal climate and energy saving potential in view of human thermal perception of the indoor environment. The study herein explores the occupant acceptability of air movements and perceived indoor air quality. Thirty-six participants were exposed to three room air temperatures (nominal: 22.5℃, 25.5℃ and 28.5℃) with each having four air speed conditions (nominal: < 0.15 m/s under mixing ventilation (MV) and 0.4, 0.6 and 0.8 m/s under IAJS) measured at the breathing height (1.1 m). The results show that participants preferred low air movements at lower temperatures and high air movements at higher temperatures. A model to predict percentage satisfied with intermittent air movements was developed. The model predicts that 87% of occupants, in compliance with ASHRAE 55-2013 standard, will find intermittent air movements acceptable between 23.7℃ and 29.1℃ within an air speed range of 0.4 to 0.8 m/s. IAJS also improved participants' perception of air quality in conditions deemed poor under MV. The findings support the potential of IAJS as a primary ventilation system in high occupant spaces such as classrooms.

Place, publisher, year, edition, pages
Sage Publications, 2019
Keywords
Intermittent air jets, Air movement acceptability, Perceived air quality, High occupant density
National Category
Building Technologies
Identifiers
urn:nbn:se:umu:diva-139730 (URN)10.1177/1420326X17732613 (DOI)000454140000006 ()
Note

Article first published online: September 20, 2017.

Available from: 2017-09-20 Created: 2017-09-20 Last updated: 2019-01-15Bibliographically approved
Yang, B., Cheng, X., Dai, D., Olofsson, T., Li, H. & Meier, A. (2019). Real-time and contactless measurements of thermal discomfort based on human poses for energy efficient control of buildings. Building and Environment, 162, Article ID 106284.
Open this publication in new window or tab >>Real-time and contactless measurements of thermal discomfort based on human poses for energy efficient control of buildings
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2019 (English)In: Building and Environment, ISSN 0360-1323, E-ISSN 1873-684X, Vol. 162, article id 106284Article in journal (Refereed) Published
Abstract [en]

Individual thermal discomfort perception gives important feedback signals for energy efficient control of building heating, ventilation and air conditioning systems. However, there is few effective method to measure thermal discomfort status of occupants in a real-time and contactless way. A novel method based on contactless measurements of human thermal discomfort status was presented. Images of occupant poses, which are related to thermoregulation mechanisms, were captured by a digital camera and the corresponding 2D coordinates were obtained. These poses were converted into skeletal configurations. An algorithm was developed to recognize different poses related to thermal discomfort, such as hugging oneself or wiping sweat off the brow. The algorithm could recognize twelve thermal discomfort related human poses. These poses were derived from a questionnaire survey of 369 human subjects. Some other human subjects participated in the validation experiments of the proposed method. All twelve thermal discomfort related poses can be recognized effectively.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Contactless measurement, Thermal discomfort, Human pose, Machine learning
National Category
Building Technologies
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-163213 (URN)10.1016/j.buildenv.2019.106284 (DOI)2-s2.0-85070109030 (Scopus ID)
Available from: 2019-09-10 Created: 2019-09-10 Last updated: 2019-09-13Bibliographically approved
Cheng, X., Yang, B., Liu, G., Olofsson, T. & Li, H. (2018). A total bounded variation approach to low visibility estimation on expressways. Sensors, 18(2), Article ID 392.
Open this publication in new window or tab >>A total bounded variation approach to low visibility estimation on expressways
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2018 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 2, article id 392Article in journal, Editorial material (Refereed) Published
Abstract [en]

Low visibility on expressways caused by heavy fog and haze is a main reason for traffic accidents. Real-time estimation of atmospheric visibility is an effective way to reduce traffic accident rates. With the development of computer technology, estimating atmospheric visibility via computer vision becomes a research focus. However, the estimation accuracy should be enhanced since fog and haze are complex and time-varying. In this paper, a total bounded variation (TBV) approach to estimate low visibility (less than 300 m) is introduced. Surveillance images of fog and haze are processed as blurred images (pseudo-blurred images), while the surveillance images at selected road points on sunny days are handled as clear images, when considering fog and haze as noise superimposed on the clear images. By combining image spectrum and TBV, the features of foggy and hazy images can be extracted. The extraction results are compared with features of images on sunny days. Firstly, the low visibility surveillance images can be filtered out according to spectrum features of foggy and hazy images. For foggy and hazy images with visibility less than 300 m, the high-frequency coefficient ratio of Fourier (discrete cosine) transform is less than 20%, while the low-frequency coefficient ratio is between 100% and 120%. Secondly, the relationship between TBV and real visibility is established based on machine learning and piecewise stationary time series analysis. The established piecewise function can be used for visibility estimation. Finally, the visibility estimation approach proposed is validated based on real surveillance video data. The validation results are compared with the results of image contrast model. Besides, the big video data are collected from the Tongqi expressway, Jiangsu, China. A total of 1,782,000 frames were used and the relative errors of the approach proposed are less than 10%.

Place, publisher, year, edition, pages
MDPI, 2018
Keywords
total bounded variation, image spectrum, low visibility estimation, piece stationary, fog and haze
National Category
Environmental Analysis and Construction Information Technology Remote Sensing
Identifiers
urn:nbn:se:umu:diva-144176 (URN)10.3390/s18020392 (DOI)000427544000075 ()29382181 (PubMedID)
Available from: 2018-01-24 Created: 2018-01-24 Last updated: 2018-06-09Bibliographically approved
Cheng, X., Yang, B., Liu, G., Olofsson, T. & Li, H. (2018). A variational approach to atmospheric visibility estimation in the weather of fog and haze. Sustainable cities and society, 39, 215-224
Open this publication in new window or tab >>A variational approach to atmospheric visibility estimation in the weather of fog and haze
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2018 (English)In: Sustainable cities and society, ISSN 2210-6707, Vol. 39, p. 215-224Article in journal (Refereed) Published
Abstract [en]

Real-time atmospheric visibility estimation in foggy and hazy weather plays a crucial role in ensuring traffic safety. Overcoming the inherent drawbacks with traditional optical estimation methods, like limited sampling volume and high cost, vision-based approaches have received much more attention in recent research on atmospheric visibility estimation. Based on the classical Koschmieder's formula, atmospheric visibility estimation is carried out by extracting an inherent extinction coefficient. In this paper we present a variational framework to handle the nature of time-varying extinction coefficient and develop a novel algorithm of extracting the extinction coefficient through a piecewise functional fitting of observed luminance curves. The developed algorithm is validated and evaluated with a big database of road traffic video from Tongqi expressway (in China). The test results are very encouraging and show that the proposed algorithm could achieve an estimation error rate of 10%. More significantly, it is the first time that the effectiveness of Koschmieder's formula in atmospheric visibility estimation was validated with a big dataset, which contains more than two million luminance curves extracted from real-world traffic video surveillance data.

Keywords
Atmospheric visibility estimation, Variational approach, Piecewise stationary time series, Computer vision, Fog and haze
National Category
Other Environmental Engineering
Identifiers
urn:nbn:se:umu:diva-144561 (URN)10.1016/j.scs.2018.02.001 (DOI)000433169800020 ()
Available from: 2018-02-06 Created: 2018-02-06 Last updated: 2018-09-05Bibliographically approved
Yang, B., Lin, Z. & Li, A. (2018). Advanced ventilation systems − theory, practice, limitations and solutions (Editorial). Trends in Civil Engineering and Material Science
Open this publication in new window or tab >>Advanced ventilation systems − theory, practice, limitations and solutions (Editorial)
2018 (English)In: Trends in Civil Engineering and Material ScienceArticle in journal, Editorial material (Refereed) Published
National Category
Building Technologies
Identifiers
urn:nbn:se:umu:diva-144300 (URN)
Available from: 2018-01-30 Created: 2018-01-30 Last updated: 2018-06-09
Dong, J., Zhang, L., Deng, S., Yang, B. & Huang, S. (2018). An experimental study on a novel radiant-convective heating system based on air source heat pump. Energy and Buildings, 158, 812-821
Open this publication in new window or tab >>An experimental study on a novel radiant-convective heating system based on air source heat pump
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2018 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 158, p. 812-821Article in journal (Refereed) Published
Abstract [en]

Air source heat pump (ASHP) has been widely applied to many parts of the world due to its simple structure and low initial cost. To save energy consumed for spacing heating and enhance the indoor thermal environment, improving the performances of ASHP has become one of the research focus in the relevant field. Currently, the most conventional heating terminal of ASHP system for spacing heating is finned tube heat exchanger coupled with air fan, which may cause strong draught sensation and dry eye problem and make users feel uncomfortable during convective heating. On the other hand, radiant heating is attracting more and more attention due to its comfortable indoor thermal environment. In this paper, a novel radiant-convective heating terminal was presented and coupled into an ASHP system. Both the operating characteristics and heating performances of the novel system were experimentally investigated. The experimental results showed that the novel system took about 28 min to enter a steady operating stage, during which the radiant panel surface temperature and outlet air temperature for the novel heating terminal, and COP of the novel system were 40.9 degrees C, 32.1 degrees C, and 3.11, respectively, under a standard heating condition. In addition, all parameters mentioned above saw a linear increase when the outdoor air temperature increased from -4.0 to 10.0 degrees C, and their respective rising rates were 0.41 degrees C, 0.28 degrees C and 0.04 per increased outdoor air temperature. Furthermore, the experimental results also demonstrated that adjusting the indoor air flow rate could effectively allocate the amount of heat generated by different heat transfer modes, which may have significant effects on the indoor thermal environment.

Keywords
Experimental study, Radiant heating, Convective heating, Air source heat pump
National Category
Civil Engineering Building Technologies
Identifiers
urn:nbn:se:umu:diva-141055 (URN)10.1016/j.enbuild.2017.10.065 (DOI)000423636600069 ()
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2018-06-09Bibliographically approved
Cheng, X., Yang, B., Liu, G., Olofsson, T. & Li, H. (2018). Atmospheric visibility detection based on total variation and piecewise stationary time series for fog and haze weather. Sustainable cities and society
Open this publication in new window or tab >>Atmospheric visibility detection based on total variation and piecewise stationary time series for fog and haze weather
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2018 (English)In: Sustainable cities and society, ISSN 2210-6707Article in journal, Editorial material (Refereed) Published
National Category
Building Technologies
Identifiers
urn:nbn:se:umu:diva-144382 (URN)
Available from: 2018-02-01 Created: 2018-02-01 Last updated: 2018-06-09
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