Biometeorological indices explain outside dwelling patterns based on Wi-Fi data in support of sustainable urban planning

Reinhart, Christoph; Dhariwal, Jay; Gero, Katy Ilonka

doi:10.1016/j.buildenv.2017.10.026

Cited by 18 publications

(8 citation statements)

References 22 publications

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“…In the present study, we analyzed the following bioclimatic indices: the equivalent temperature (TeK), the Effective Temperature (TE), the Cooling Power (H), the Universal Thermal Climate Index (UTCI), and the Temperature-Humidity Index (THI). They are largely used for the bioclimatic conditions assessment in different regions [18,20,23,[47][48][49]. For some cities in Romania, these indicators were calculated and presented in other short studies [50,51].…”

Section: Biometeorological Indicesmentioning

confidence: 99%

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Changes Detected in Five Bioclimatic Indices in Large Romanian Cities over the Period 1961–2016

et al. 2020

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Bioclimatic indices are very important tools to evaluate the thermal stress of the human body. The aims of this study were to analyze the general bioclimatic conditions in ten big cities in Romania and to find out if there has been any change in five bioclimatic indices over a 56‑year period: 1961–2016. The indices considered were: equivalent temperature, effective temperature, cooling power, universal thermal climate index and temperature-humidity index. They were calculated based on the daily meteorological data of air temperature, relative humidity, and wind speed recorded in 10 weather stations in Romania: Bucharest-Băneasa, Botoșani, Cluj-Napoca, Constanța, Craiova, Galați, Iași, Oradea, Sibiu and Timișoara. The features investigated for trend detection consisted of the frequency and length of the occurrence period for each class and for each index. The test used for trend detection was Mann-Kendall and the magnitude of the trend (the slope) was calculated by employing Sen’s slope method. The main results are based on frequency analysis. Three indices showed comfort class as dominant whereas the other two indicated cold stress conditions as dominant in the area. There was a shift from the cold stress conditions to the warm and hot ones for all the indices. The most stressful conditions for hot extremes did not indicate significant change. The climate in the big cities of Romania became milder during the cold season and hotter during the warm period of the year. The analysis of the length of each thermal class indicated mainly longer occurrence periods during the year for comfortable or warm stress classes.

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Section: Biometeorological Indicesmentioning

confidence: 99%

“…Two comprehensive reviews have been developed [11,12], whereas some other research papers focused on specific issues. The great majority of these studies have focused on thermal sensations in urban areas [1,[13][14][15][16][17][18][19][20][21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Changes Detected in Five Bioclimatic Indices in Large Romanian Cities over the Period 1961–2016

et al. 2020

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“…First, IoT technologies have enabled the assessment of thermal comfort on human activity and behavior in the built environment. For instance, in addition to environmental measurements, Wi-Fi connectivity data in outdoor spaces have been used to obtain real-time occupancy data and to explain outside dwelling patterns modified by thermal environments (Reinhart et al, 2017;Dhariwal et al, 2019). Using Wi-fi scanners in public courtyards, Reinhart et al (2017) recorded occupancy patterns over 10-month in addition to measurements of air temperature, relative humidity, wind speed and direction, and solar radiation.…”

Section: Outdoor Iot Sensing Of the Thermal Environmentmentioning

confidence: 99%

“…For instance, in addition to environmental measurements, Wi-Fi connectivity data in outdoor spaces have been used to obtain real-time occupancy data and to explain outside dwelling patterns modified by thermal environments (Reinhart et al, 2017;Dhariwal et al, 2019). Using Wi-fi scanners in public courtyards, Reinhart et al (2017) recorded occupancy patterns over 10-month in addition to measurements of air temperature, relative humidity, wind speed and direction, and solar radiation. The thermal environment (characterized by biometeorological thermal comfort indices) was found to strongly correlate with lunch-time activity by regular users.…”

Section: Outdoor Iot Sensing Of the Thermal Environmentmentioning

confidence: 99%

Transformational IoT sensing for air pollution and thermal exposures

Pantelic

Nazarian

Miller

et al. 2022

Front. Built Environ.

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Cities today encounter significant challenges pertaining to urbanization and population growth, resource availability, and climate change. Concurrently, unparalleled datasets are generated through Internet of Things (IoT) sensing implemented at urban, building, and personal scales that serve as a potential tool for understanding and overcoming these issues. Focusing on air pollution and thermal exposure challenges in cities, we reviewed and summarized the literature on IoT environmental sensing on urban, building, and human scales, presenting the first integrated assessment of IoT solutions from the data convergence perspective on all three scales. We identified that there is a lack of guidance on what to measure, where to measure, how frequently to measure, and standards for the acceptable measurement quality on all scales of application. The current literature review identified a significant disconnect between applications on each scale. Currently, the research primarily considers urban, building, and personal scale in isolation, leading to significant data underutilization. We addressed the scientific and technological challenges and opportunities related to data convergence across scales and detailed future directions of IoT sensing along with short- and long-term research and engineering needs. IoT application on a personal scale and integration of information on all scales opens up the possibility of developing personal thermal comfort and exposure models. The development of personal models is a vital promising area that offers significant advancements in understanding the relationship between environment and people that requires significant further research.

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“…Steady-state models, such as the PMV (Predicted Mean Vote) index, may not be appropriate for the assessment of short-term outdoor thermal comfort, mainly because they are unable to analyse transient exposure (63). UTCI was chosen in many studies and was found to affect respondents' feelings, attendance, and choice significantly (11,66,128). Moreover, such behavioral responses to the thermal environment were found to differ by gender, age, and types of activities (157).…”

Section: Microclimate or Specific Outdoor Thermal Parametersmentioning

confidence: 99%

A Systematic Review of Objective Factors Influencing Behavior in Public Open Spaces

Han

Song

et al. 2022

Front. Public Health

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As a significant part of outdoor built-environment, public open spaces are closely associated with people's daily lives. Studies of outdoor behavior in these spaces can shed light on users' environmental perceptions and contribute to the promotion of physiological and psychological health. Many recent studies are case studies focused where observations, surveys and interviews have been conducted to understand the factors influencing people's behavior on one or few sites or city environments. There have been few reviews related to this topic, and none have been based on the systematic understanding of influencing factors. This paper presents a systematic review of interactions between behavior and the built environment in public open spaces, and highlights the impacts of diverse and objective influencing factors. Followed the rules of PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), 109 papers published in 2000–2021 were selected and reviewed. The distribution of the studied interactions is analyzed, and the impacts of four distinct factors: personal background, location and context, environmental component, and climate stimuli, are extracted, categorized, and specified. Moreover, outdoor health benefits are discussed based on which, crucial factors that require emphasis after the outbreak of COVID-19 are identified. Throughout this paper, behavioral influencing processes, including objective influencing factors, subjective feedback, and the relationships involved, are considered to provide a comprehensive picture. With the robust classification of existing factors, architects, urban designers, policy makers and fellow researches could be easier to get a more comprehensive trend from the past. This paper also provides guidance for future research, especially given that COVID-19 has created huge changes to outdoor needs and customary behavior.Systematic Review Registration:http://www.prisma-statement.org/.

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Biometeorological indices explain outside dwelling patterns based on Wi-Fi data in support of sustainable urban planning

Cited by 18 publications

References 22 publications

Changes Detected in Five Bioclimatic Indices in Large Romanian Cities over the Period 1961–2016

Changes Detected in Five Bioclimatic Indices in Large Romanian Cities over the Period 1961–2016

Transformational IoT sensing for air pollution and thermal exposures

A Systematic Review of Objective Factors Influencing Behavior in Public Open Spaces

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