Italy was the first country in Europe to enter lock-down due to COVID-19 pandemic. Most employees have been forced to adopt a work at home solution to avoid any possibility of spreading the virus. The article presents the results of a survey carried out in March-June 2020, during the first lockdown in Italy, aimed at investigating how people perceive the Indoor Environmental Quality (IEQ) of their households during working from home. The questionnaire consists in a general section reporting information about participant, households and rooms where they perform the working activities; a specific section reporting feedbacks on each IEQ aspects (thermal, visual comfort, air and acoustic quality), overall comfort, productivity and other external variables that can affect users' well-being during working hours. A total of 330 participants from all over the Italian territory signed the consent to participate in the survey over a period of about 3 months. The dataset was used to define the global level of satisfaction, perception, preference and interference with work at home, considering the main indoor environmental factors. The Machine Learning (ML) approach was applied to identify the most useful model to predict the overall comfort satisfaction.
A survey-based approach used to analyse the indoor satisfaction and productivity level of user in smart working during lock-down due to the COVID-19 pandemic
Francesco Salamone
;Lorenzo Belussi;Ludovico Danza;Italo Meroni
2021
Abstract
Italy was the first country in Europe to enter lock-down due to COVID-19 pandemic. Most employees have been forced to adopt a work at home solution to avoid any possibility of spreading the virus. The article presents the results of a survey carried out in March-June 2020, during the first lockdown in Italy, aimed at investigating how people perceive the Indoor Environmental Quality (IEQ) of their households during working from home. The questionnaire consists in a general section reporting information about participant, households and rooms where they perform the working activities; a specific section reporting feedbacks on each IEQ aspects (thermal, visual comfort, air and acoustic quality), overall comfort, productivity and other external variables that can affect users' well-being during working hours. A total of 330 participants from all over the Italian territory signed the consent to participate in the survey over a period of about 3 months. The dataset was used to define the global level of satisfaction, perception, preference and interference with work at home, considering the main indoor environmental factors. The Machine Learning (ML) approach was applied to identify the most useful model to predict the overall comfort satisfaction.File | Dimensione | Formato | |
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