Thermal Comfort and Satisfaction in the Context of Social Housing: Case Study in Bogotá, Colombia

Bernal, C.; Medina, Juan Gallego; Pinzón, Andrés

doi:10.21315/jcdc2019.24.1.6

Cited by 8 publications

(12 citation statements)

References 19 publications

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“…This consisted of a new housing complex representative of the majority of social housing projects built in Bogotá in the past decade. It featured 456 apartments in 19 six-storey towers with four apartments per level [38]. The project was divided into two stages, during the first one, a sample of 44 apartments distributed on different floors and towers was evaluated.…”

Section: Project Onementioning

confidence: 99%

The Importance of Standardised Data-Collection Methods in the Improvement of Thermal Comfort Assessment Models for Developing Countries in the Tropics

et al. 2019

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Thermal comfort in the built environment is one of the most defining parameters influencing energy use, environmental quality, and occupant satisfaction. Unfortunately, there is a lack of research in this area within developing countries, which are becoming increasingly urbanised and where mechanical air conditioning demands are rising. Many of these countries are adopting thermal comfort standards such as the ASHRAE Standard 55, the EN 15251, and the ISO 7730 to regulate the use of air-conditioning; even when these standards have been widely criticised for their inadequacy within geographical regions different to the ones that they were designed for. Research suggests the need to confirm these models through further post-occupancy studies and fieldwork. Deficiencies in data collection and methodologies are thought to require particular attention to develop algorithms that can predict thermal comfort levels accurately. Comprehensive strategies considering interrelated psychological, physiological and social factors are needed. This manuscript highlights gaps of research, specifically within tropical developing countries, through the analysis of Colombia as a case study. It emphasises the importance of standardised fieldwork data and gives examples of alternative collection systems. This aims to contribute to the understanding of occupant´s adaptive behaviours and their impact on the mitigation of climate change.

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Section: Project Onementioning

confidence: 99%

The Importance of Standardised Data-Collection Methods in the Improvement of Thermal Comfort Assessment Models for Developing Countries in the Tropics

et al. 2019

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“…Occupancy knowledge, on the other hand, is difficult to come by since a big amount of data that may be utilized as ground truth is not always accessible, and alternative learning techniques are in high demand [24]. Despite a wide range of possible applications, building occupancy estimation remains a time-consuming, errorprone, and costly procedure [25]. [26] provided a comprehensive literature analysis for real-time monitoring systems and modeling in office buildings.…”

Section: Related Workmentioning

confidence: 99%

“…Short-term occupancy forecast for single rooms is difficult due to the stochastic nature of the occupation. Previous occupant model studies have utilized binary data (i.e., presence and absence) [30], exact discrete values (i.e., the number of occupants) [24], or normal distribution ranges (i.e., the number of occupants) [25] to represent various levels of occupant behavior detail. Based on the application context, each of these simulations accomplished a decent trade between model accuracy and intricacy.…”

Section: Related Workmentioning

confidence: 99%

Detecting occupancy behaviour of buildings through environment monitoring sensing

Yahaya¹,

Usman²,

Uwa³

2022

World J. Adv. Res. Rev.

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The goal of this research is to produce a realistic occupancy forecast as well as an ideal occupancy-based controller for increasing the performance of Heating Ventilation and Air-Conditioning [HVAC] systems. Reliable occupancy prediction is a critical enabler for demand-based HVAC control since it ensures that the HVAC system is not running unnecessarily while a room or zone is empty. We present simple yet successful occupancy prediction methods, as well as an approach for automatically setting temperature set-points, in this work. We present three alternative occupancy prediction algorithms based on historical occupancy measurements. The proposed approach uses historical occupancy profile and environmental room data to establish an occupancy identity strategy that can provide a stochastic model based on uncertain basis functions as an alternative. According to the findings, the proposed occupancy prediction algorithms could reach an accuracy of approximately 85% reliable prediction with few negative predictions.

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“…In Latin America, locations with a similar climate to the Meseta [24,25] show most comfort votes below the comfort band suggested by the ASHRAE 55 standard [13]. Similarities in culture and building practices with Mexico and the Meseta suggest a similar performance.…”

Section: Field Studiesmentioning

confidence: 99%

Thermal comfort in naturally ventilated dwellings in the central Mexican plateau

Zepeda-Gil

Natarajan

2022

Building and Environment

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Thermal Comfort and Satisfaction in the Context of Social Housing: Case Study in Bogotá, Colombia

Cited by 8 publications

References 19 publications

The Importance of Standardised Data-Collection Methods in the Improvement of Thermal Comfort Assessment Models for Developing Countries in the Tropics

The Importance of Standardised Data-Collection Methods in the Improvement of Thermal Comfort Assessment Models for Developing Countries in the Tropics

Detecting occupancy behaviour of buildings through environment monitoring sensing

Thermal comfort in naturally ventilated dwellings in the central Mexican plateau

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