Pub Date : 2022-02-06DOI: 10.1080/17508975.2022.2028598
P. Roelofsen, Kaspar M. B. Jansen, P. Vink
{"title":"A larger statistical basis and a wider application area of a re-derived PPD equation in the (NEN-)EN-ISO 7730 model","authors":"P. Roelofsen, Kaspar M. B. Jansen, P. Vink","doi":"10.1080/17508975.2022.2028598","DOIUrl":"https://doi.org/10.1080/17508975.2022.2028598","url":null,"abstract":"","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45424508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-29DOI: 10.1080/17508975.2021.2011702
Esa Halmetoja, H. Salonen, Heikki Ihasalo, Kary Främling
ABSTRACT This research assesses whether the perceived indoor air quality (IAQ) can be improved with additional sensors in older buildings. The research does not investigate IAQ in its broadest sense, but focus on phenomena perceived by the human senses, such as thermal comfort. The effects of the maintenance of technical systems on perceived IAQ are also studied. In the study, 2506 sensors were installed in 29 public buildings in nine cities in Finland. The change in studied indicators was measured over four years and compared to 65 buildings in the comparison group. The study provides an objective view of the usefulness of BAS-connected and cloud-based sensors. The study also shows that a building owner considering introducing cloud technology to improve perceived IAQ should also be prepared to reform property maintenance processes. The study showed that additional sensors connected to the BAS improve thermal stability. No such improvement was observed in sensors connected to cloud services.
{"title":"Critical study of the applicability of additional IAQ sensors in older buildings","authors":"Esa Halmetoja, H. Salonen, Heikki Ihasalo, Kary Främling","doi":"10.1080/17508975.2021.2011702","DOIUrl":"https://doi.org/10.1080/17508975.2021.2011702","url":null,"abstract":"ABSTRACT This research assesses whether the perceived indoor air quality (IAQ) can be improved with additional sensors in older buildings. The research does not investigate IAQ in its broadest sense, but focus on phenomena perceived by the human senses, such as thermal comfort. The effects of the maintenance of technical systems on perceived IAQ are also studied. In the study, 2506 sensors were installed in 29 public buildings in nine cities in Finland. The change in studied indicators was measured over four years and compared to 65 buildings in the comparison group. The study provides an objective view of the usefulness of BAS-connected and cloud-based sensors. The study also shows that a building owner considering introducing cloud technology to improve perceived IAQ should also be prepared to reform property maintenance processes. The study showed that additional sensors connected to the BAS improve thermal stability. No such improvement was observed in sensors connected to cloud services.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47136506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-08DOI: 10.1080/17508975.2021.1997702
A. Ackley, M. Donn, G. Thomas
ABSTRACT The New Zealand Ministry of Education has a single electronic monitoring device (sensor) that simultaneously measures five environmental elements (light, temperature, relative humidity, noise, and carbon dioxide levels) in some schools. The aim is to develop an indoor environment monitoring protocol to inform proactive assets management of school buildings. This study used observations and actual measurements of these environmental variables in three typical classrooms in three schools, to assess whether the use of a one-point sensor in one location could predict the thermal condition across a classroom. The results revealed that a single sensor located at a height of 1.5 m on an unglazed vertical wall with a low thermal mass, and away from direct sunlight, heating and cooling systems, and drafts from open windows can be used to identify good and poor thermal conditions in classrooms. A one-point sensor provides a general indication of the thermal performance of a room, but not the thermal variations across the room. This study provides a systematic method for using a single sensor to monitor thermal performance in a large school property portfolio for early discrimination from hundreds or more classrooms to direct thermal intervention programmes for large groups of school buildings.
{"title":"Monitoring indoor thermal performance in a National School Property Portfolio","authors":"A. Ackley, M. Donn, G. Thomas","doi":"10.1080/17508975.2021.1997702","DOIUrl":"https://doi.org/10.1080/17508975.2021.1997702","url":null,"abstract":"ABSTRACT The New Zealand Ministry of Education has a single electronic monitoring device (sensor) that simultaneously measures five environmental elements (light, temperature, relative humidity, noise, and carbon dioxide levels) in some schools. The aim is to develop an indoor environment monitoring protocol to inform proactive assets management of school buildings. This study used observations and actual measurements of these environmental variables in three typical classrooms in three schools, to assess whether the use of a one-point sensor in one location could predict the thermal condition across a classroom. The results revealed that a single sensor located at a height of 1.5 m on an unglazed vertical wall with a low thermal mass, and away from direct sunlight, heating and cooling systems, and drafts from open windows can be used to identify good and poor thermal conditions in classrooms. A one-point sensor provides a general indication of the thermal performance of a room, but not the thermal variations across the room. This study provides a systematic method for using a single sensor to monitor thermal performance in a large school property portfolio for early discrimination from hundreds or more classrooms to direct thermal intervention programmes for large groups of school buildings.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44182434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-02DOI: 10.1080/17508975.2021.2004385
Kurtis Harley Looby, S. Smith, Mehdi Shahrestani
ABSTRACT Offsite prefabrication (OP) is an important approach in overcoming some inefficiencies in the U.K. construction sector. Whilst growth in OP can be demonstrated, its uptake is limited in relation to the expected benefit of its application. Perception, in part due to historical application, has been highlighted as a significant contributing factor in its limited uptake. However, despite recognition that the uncertainties associated with perception on OP are important to technological innovation adoption, these uncertainties were not explored in the previous studies. We adopt fuzzy-set theory, in combination with a survey from 76 organisations in the U.K., to explore these uncertainties in perception for a broad range of OP applications. Through fuzzy-set analysis, the study presents insight into some of the uncertainties related to the perception of OP through three themes: Uptake, Impression, and Strategy. This study proposes that the uncertainty in the perception of OP value, within specific and across all applications, needs to be explicitly considered to understand how perception is informing uptake. This research also suggests that negative perception is one of the key constraints to uptake and it is in fact the overall culture of the U.K. construction sector that is limiting the uptake of OP.
{"title":"Attitudes towards offsite prefabrication: a fuzzy approach to examining uncertainty within U.K. industry perception","authors":"Kurtis Harley Looby, S. Smith, Mehdi Shahrestani","doi":"10.1080/17508975.2021.2004385","DOIUrl":"https://doi.org/10.1080/17508975.2021.2004385","url":null,"abstract":"ABSTRACT Offsite prefabrication (OP) is an important approach in overcoming some inefficiencies in the U.K. construction sector. Whilst growth in OP can be demonstrated, its uptake is limited in relation to the expected benefit of its application. Perception, in part due to historical application, has been highlighted as a significant contributing factor in its limited uptake. However, despite recognition that the uncertainties associated with perception on OP are important to technological innovation adoption, these uncertainties were not explored in the previous studies. We adopt fuzzy-set theory, in combination with a survey from 76 organisations in the U.K., to explore these uncertainties in perception for a broad range of OP applications. Through fuzzy-set analysis, the study presents insight into some of the uncertainties related to the perception of OP through three themes: Uptake, Impression, and Strategy. This study proposes that the uncertainty in the perception of OP value, within specific and across all applications, needs to be explicitly considered to understand how perception is informing uptake. This research also suggests that negative perception is one of the key constraints to uptake and it is in fact the overall culture of the U.K. construction sector that is limiting the uptake of OP.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46440123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-08DOI: 10.1080/17508975.2021.1985418
D. Pereira, Rui Castro, P. Adão
ABSTRACT This research proposes an investigation on the problem of detecting and predicting occupancy by using solely readily available electricity consumption data, obtained from smart metres. The following research questions are defined: (1) Is it possible to predict occupancy by using solely electricity consumption data?; (2) Is it possible to use a single classification model to monitor occupancy in multiple households? The findings show that an occupancy detection accuracy of up to 92% can be achieved by using solely electricity consumption data. The problem of generalizing the classification model, i.e. using a single classification model to monitor occupancy in multiple households, is also addressed. It is found that an occupancy detection accuracy of up to 83% is achievable in this case. Regarding occupancy prediction, occupancy in multiple households with an accuracy of up to 75% is obtained, by using solely electricity consumption data. For both occupancy monitoring and prediction, it is found that households with a low level of occupancy can benefit more from these systems.
{"title":"Occupancy detection and prediction from electricity consumption data in smart homes: application to a Portuguese case-study","authors":"D. Pereira, Rui Castro, P. Adão","doi":"10.1080/17508975.2021.1985418","DOIUrl":"https://doi.org/10.1080/17508975.2021.1985418","url":null,"abstract":"ABSTRACT\u0000 This research proposes an investigation on the problem of detecting and predicting occupancy by using solely readily available electricity consumption data, obtained from smart metres. The following research questions are defined: (1) Is it possible to predict occupancy by using solely electricity consumption data?; (2) Is it possible to use a single classification model to monitor occupancy in multiple households? The findings show that an occupancy detection accuracy of up to 92% can be achieved by using solely electricity consumption data. The problem of generalizing the classification model, i.e. using a single classification model to monitor occupancy in multiple households, is also addressed. It is found that an occupancy detection accuracy of up to 83% is achievable in this case. Regarding occupancy prediction, occupancy in multiple households with an accuracy of up to 75% is obtained, by using solely electricity consumption data. For both occupancy monitoring and prediction, it is found that households with a low level of occupancy can benefit more from these systems.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42197675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-27DOI: 10.1080/17508975.2021.1964424
P. Bluyssen, Dadi Zhang, M. Ortiz
ABSTRACT Next to personal, psychosocial and physiological aspects, environmental aspects of homes may affect the health and comfort of their occupants. This study aimed to investigate the multifactorial character of both rhinitis and headaches among five groups of students from universities in five different cities: Taichung (Taiwan), Concepcion (Chile), Paramaribo (Suriname), Beijing (China) and Delft (The Netherlands). Among the students studied, 18% declared having suffered from rhinitis in the last 12 months, and 30% from headaches in the last 3 months. Self-reported characteristics of 682 students and their homes were linked to self-reported rhinitis and headaches. Logistic regression modelling was applied to explore relations between building-related factors and rhinitis, and between building-related factors and headaches. After full adjustment, the regression model for both rhinitis and headaches confirmed their multifactorial character. While personal-related factors family rhinitis and age were associated with rhinitis, negative events and PANAS negative were with headaches. Biological pollutants (caused by pets) were associated both with rhinitis and headaches; chemical pollutants, caused by open bookshelves and lack of sweeping floors, were associated with rhinitis. The study concludes that the identified risk factors seemed independent of season or climate region.
{"title":"Self-reported rhinitis and headaches of students from universities in Taiwan, Chile, Suriname, China and the Netherlands, and its association with their home environment","authors":"P. Bluyssen, Dadi Zhang, M. Ortiz","doi":"10.1080/17508975.2021.1964424","DOIUrl":"https://doi.org/10.1080/17508975.2021.1964424","url":null,"abstract":"ABSTRACT Next to personal, psychosocial and physiological aspects, environmental aspects of homes may affect the health and comfort of their occupants. This study aimed to investigate the multifactorial character of both rhinitis and headaches among five groups of students from universities in five different cities: Taichung (Taiwan), Concepcion (Chile), Paramaribo (Suriname), Beijing (China) and Delft (The Netherlands). Among the students studied, 18% declared having suffered from rhinitis in the last 12 months, and 30% from headaches in the last 3 months. Self-reported characteristics of 682 students and their homes were linked to self-reported rhinitis and headaches. Logistic regression modelling was applied to explore relations between building-related factors and rhinitis, and between building-related factors and headaches. After full adjustment, the regression model for both rhinitis and headaches confirmed their multifactorial character. While personal-related factors family rhinitis and age were associated with rhinitis, negative events and PANAS negative were with headaches. Biological pollutants (caused by pets) were associated both with rhinitis and headaches; chemical pollutants, caused by open bookshelves and lack of sweeping floors, were associated with rhinitis. The study concludes that the identified risk factors seemed independent of season or climate region.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42543278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-22DOI: 10.1080/17508975.2021.1962783
A. B. Obayomi, O. T. Ogunbayo
ABSTRACT The underlying factors of housing research emanate from the fact that people's lives and well-being rely on the quality of the house and the surroundings where it is situated. Housing satisfaction goes beyond brick and mortar and aesthetics. It examines housing attributes that are not already visible to the eyes that could influence the occupants’ satisfaction with such buildings. This study investigated user's satisfaction with private housing estates using the Analytical Hierarchy Process (AHP). The research is imperative because most studies in Nigeria focused mainly on government-owned or social housing satisfaction. While private housing estates have received little attention over the years. 280 questionnaires were randomly distributed to the building occupants within the estates under consideration based on their level of availability during the 13 weeks surveyed periods. From the survey, the top-ranked factors that influence user satisfaction were utility adequacy, infrastructural, provision of facilities, and maintenance factors with the priority weight of 0.425, 0.235, and 0.203 accordingly. Therefore, real estate practitioners and housing developers must take these housing attributes into proper consideration to promoting a better quality of living, enhancing building performance that could increase the total return on investment, and meet the overall user satisfaction.
{"title":"User’s satisfaction with private housing estates in Abuja using Analytical Hierarchy Process (AHP)","authors":"A. B. Obayomi, O. T. Ogunbayo","doi":"10.1080/17508975.2021.1962783","DOIUrl":"https://doi.org/10.1080/17508975.2021.1962783","url":null,"abstract":"ABSTRACT The underlying factors of housing research emanate from the fact that people's lives and well-being rely on the quality of the house and the surroundings where it is situated. Housing satisfaction goes beyond brick and mortar and aesthetics. It examines housing attributes that are not already visible to the eyes that could influence the occupants’ satisfaction with such buildings. This study investigated user's satisfaction with private housing estates using the Analytical Hierarchy Process (AHP). The research is imperative because most studies in Nigeria focused mainly on government-owned or social housing satisfaction. While private housing estates have received little attention over the years. 280 questionnaires were randomly distributed to the building occupants within the estates under consideration based on their level of availability during the 13 weeks surveyed periods. From the survey, the top-ranked factors that influence user satisfaction were utility adequacy, infrastructural, provision of facilities, and maintenance factors with the priority weight of 0.425, 0.235, and 0.203 accordingly. Therefore, real estate practitioners and housing developers must take these housing attributes into proper consideration to promoting a better quality of living, enhancing building performance that could increase the total return on investment, and meet the overall user satisfaction.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45474030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-17DOI: 10.1080/17508975.2021.1963651
Yu Fu, Tongyu Zhou, I. Lun, F. Khayatian, Wu Deng, Weiguang Su
ABSTRACT In non-air-conditioned buildings, opening or closing of windows is one of the most common behaviours that occupants tend to carry out to restore their thermal comfort. As an alternative approach to studying the occupant behaviour, particularly when it is difficult to run extensive field studies or due to limits like privacy concerns, this work explores a data-driven method to predict the window openings based on thermal comfort evaluation. The Gradient Boosting Decision Trees (GBDT) algorithm is applied to investigate the importance of selected features, including weather and main building characteristics, to the indoor thermal comfort in non-air-conditioned buildings across whole China. The training set comprises the building simulation results of 95 main cities covering all the five climate regions in China and has 828,360 groups of data in total. The predictor achieves a high accuracy of approximately 95%, and therefore enables the users to estimate the likelihood of window opening based on outdoor weather conditions and local building characteristics. As an original contribution, the study shows that conditioned upon the availability of adequate simulation data, a machine learning predictor trained solely on simulation data can accurately predict realistic window opening behaviours, without relying on any indoor measurement.
{"title":"A data-driven approach for window opening predictions in non-air-conditioned buildings","authors":"Yu Fu, Tongyu Zhou, I. Lun, F. Khayatian, Wu Deng, Weiguang Su","doi":"10.1080/17508975.2021.1963651","DOIUrl":"https://doi.org/10.1080/17508975.2021.1963651","url":null,"abstract":"ABSTRACT In non-air-conditioned buildings, opening or closing of windows is one of the most common behaviours that occupants tend to carry out to restore their thermal comfort. As an alternative approach to studying the occupant behaviour, particularly when it is difficult to run extensive field studies or due to limits like privacy concerns, this work explores a data-driven method to predict the window openings based on thermal comfort evaluation. The Gradient Boosting Decision Trees (GBDT) algorithm is applied to investigate the importance of selected features, including weather and main building characteristics, to the indoor thermal comfort in non-air-conditioned buildings across whole China. The training set comprises the building simulation results of 95 main cities covering all the five climate regions in China and has 828,360 groups of data in total. The predictor achieves a high accuracy of approximately 95%, and therefore enables the users to estimate the likelihood of window opening based on outdoor weather conditions and local building characteristics. As an original contribution, the study shows that conditioned upon the availability of adequate simulation data, a machine learning predictor trained solely on simulation data can accurately predict realistic window opening behaviours, without relying on any indoor measurement.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43421690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-13DOI: 10.1080/17508975.2021.1962785
P. Roelofsen, Kaspar M. B. Jansen, P. Vink
ABSTRACT There are different thermal perception models linked to a mathematical thermophysiological human model, with which the thermal sensation under stationary and/or dynamic conditions can be evaluated. Each of these perception and thermophysiological models have their own field of application. Stolwijk developed a thermophysiological human model without an associated thermal perception model, which today is still the basis for other mathematical thermophysiological models. Fiala developed the FPC model, also based on the Stolwijk model, and is one of the latest developments in the field of thermophysiological human models. In the FPC model, an equation is included with which the thermal sensation under stationary and dynamic conditions can be assessed; the so-called Dynamic Thermal Sensation (DTS). The DTS equation is, however, specifically developed for use in combination with the FPC model. In contrast to the Stolwijk model, the source code of the computer programs of the later developed thermophysiological human models is not freely available, which limits the use and applicability of the models in practice. It is precise because of the availability of the source code that the Stolwijk model is still used in industry and the research world. The question, therefore, arises: ‘To what extent can a human transient thermal sensation equation be derived, combined with the Stolwijk model, in a similar way to that used for the DTS equation in the FPC model?’.
{"title":"A transient thermal sensation equation fit for the modified Stolwijk model","authors":"P. Roelofsen, Kaspar M. B. Jansen, P. Vink","doi":"10.1080/17508975.2021.1962785","DOIUrl":"https://doi.org/10.1080/17508975.2021.1962785","url":null,"abstract":"ABSTRACT There are different thermal perception models linked to a mathematical thermophysiological human model, with which the thermal sensation under stationary and/or dynamic conditions can be evaluated. Each of these perception and thermophysiological models have their own field of application. Stolwijk developed a thermophysiological human model without an associated thermal perception model, which today is still the basis for other mathematical thermophysiological models. Fiala developed the FPC model, also based on the Stolwijk model, and is one of the latest developments in the field of thermophysiological human models. In the FPC model, an equation is included with which the thermal sensation under stationary and dynamic conditions can be assessed; the so-called Dynamic Thermal Sensation (DTS). The DTS equation is, however, specifically developed for use in combination with the FPC model. In contrast to the Stolwijk model, the source code of the computer programs of the later developed thermophysiological human models is not freely available, which limits the use and applicability of the models in practice. It is precise because of the availability of the source code that the Stolwijk model is still used in industry and the research world. The question, therefore, arises: ‘To what extent can a human transient thermal sensation equation be derived, combined with the Stolwijk model, in a similar way to that used for the DTS equation in the FPC model?’.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49659929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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