Correlation of technology indicators with improving productivity and reducing energy consumption in climate housing

Subject Areas : City architect

Zahra Mehraban Sehgonbad ¹ , Mehrdad Javidinejad ² , سعید تیزقلم زنوزی ³

1 -
2 - Department of Architecture, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
3 - استادیار گروه معماری، دانشگاه آزاد اسلامی

Received: 2024-08-20 Accepted : 2024-09-17 Published : 2024-09-21

Keywords:

Abstract :

The main purpose of using these housings is to reduce energy consumption and increase comfort and efficiency. But the important point is the knowledge and technology of operating and maintaining this system in climate housing. Due to the fact that costs and financial issues are only one of the factors influencing the decision to use intelligent building management and control systems, the need to identify other factors and drivers for decision-making in this field is obvious. Meanwhile, fewer studies have addressed the understanding and recognition of the factors and efficiency criteria of the building management system in relation to the development of a complete and comprehensive evaluation model. In this regard, the main goal of the current research is the correlation of technology indicators in improving productivity and reducing energy consumption in residential houses. The current research is based on mixed (quantitative-qualitative) data in terms of applied purpose, in terms of descriptive survey research method. The data analysis in this research has two parts, in the first part, the prioritization and verification of indicators by experts and experts are discussed, in this part, the fuzzy Delphi model was used for verification and TOPSIS for prioritization. And finally, multiple regression was used to examine the relationship between variables and explain the model. The results of TOPSIS show that the intelligentization of heating and cooling energy has the first priority, the intelligentization of indoor air quality has the second rank, and the intelligentization of lighting energy consumption has the third priority. The data of the multiple correlation coefficient is 0.815 and the corrected coefficient of determination obtained is equal to 0.815 and this value shows that 81.4 percent of the changes in total energy consumption can be predicted through technology indicators. Based on the data, the calculated value of F is 588/383 greater than the critical value of F; As a result, with 99 percent certainty, it can be said that there is a significant relationship between technology indicators and total energy consumption.

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