Purpose: Workplace space utilization data reveals patterns of space usage, the occupants’ presence and mobility within the office building. Nowadays, emerging technology such as smart sensors and devices can revolutionize the measurement of space utilization data, which is originally dominated by human observers with paper and pencil. However, these novel instruments are often used in an old fashion, which restricts the exploitation of their full potential. This study aims to shed new light on the benefits and limits of using smart technology in measuring space utilization data and discusses the challenges and opportunities in analyzing the data measured by smart sensors. Design/methodology/approach: First, the literature regarding common methods and previous studies about office space utilization measurement was reviewed. Then, a data set consisting of space utilization data collected through Passive Infra-Red sensors for 35 meeting rooms in a bank building was carefully evaluated. Finally, the space utilization results based on methods calculated in two different granularities were compared. Findings: The number of occupied hours calculated at an hour level was 1.32-hour larger than that calculated at a minute level. As both results show the concept of space utilization, which was the amount of time that the space was occupied, this paper revealed a gap between the two space utilization calculation methods and further discussed the issues and challenges for future space utilization data analysis and benchmarking. Originality/value: To the best of the authors’ knowledge, this is the first study critically addressing office space utilization issues by comparing calculation methods in different granularity.
A change in granularity: measure space utilization through smart technologies
Tagliaro C.;
2021-01-01
Abstract
Purpose: Workplace space utilization data reveals patterns of space usage, the occupants’ presence and mobility within the office building. Nowadays, emerging technology such as smart sensors and devices can revolutionize the measurement of space utilization data, which is originally dominated by human observers with paper and pencil. However, these novel instruments are often used in an old fashion, which restricts the exploitation of their full potential. This study aims to shed new light on the benefits and limits of using smart technology in measuring space utilization data and discusses the challenges and opportunities in analyzing the data measured by smart sensors. Design/methodology/approach: First, the literature regarding common methods and previous studies about office space utilization measurement was reviewed. Then, a data set consisting of space utilization data collected through Passive Infra-Red sensors for 35 meeting rooms in a bank building was carefully evaluated. Finally, the space utilization results based on methods calculated in two different granularities were compared. Findings: The number of occupied hours calculated at an hour level was 1.32-hour larger than that calculated at a minute level. As both results show the concept of space utilization, which was the amount of time that the space was occupied, this paper revealed a gap between the two space utilization calculation methods and further discussed the issues and challenges for future space utilization data analysis and benchmarking. Originality/value: To the best of the authors’ knowledge, this is the first study critically addressing office space utilization issues by comparing calculation methods in different granularity.File | Dimensione | Formato | |
---|---|---|---|
Tagliaro-Zhou-Hua_2021_A Change in Granularity_10-1108_F-08-2019-0093.pdf
Accesso riservato
:
Publisher’s version
Dimensione
331.9 kB
Formato
Adobe PDF
|
331.9 kB | Adobe PDF | Visualizza/Apri |
Tagliaro_AAM.pdf
accesso aperto
:
Post-Print (DRAFT o Author’s Accepted Manuscript-AAM)
Dimensione
606.73 kB
Formato
Adobe PDF
|
606.73 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.