A comparison study on space-use analysis techniques and proposal of a novel method for determining space needs in public facilities

Rusek, Robert; Colomer, Joan; Meléndez, Joaquím

doi:10.1016/j.scs.2018.02.032

Cited by 8 publications

(6 citation statements)

References 16 publications

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“…Dataset 2 : On-site recorded occupants’ activity . In addition to the sensor-tracked occupancy data, on-site manual observation was conducted to capture occupants’ activities within the co-working space to determine how space is used [ 48 ]. Manual observation provides supplementary information to the sensor data [ 49 ].…”

Section: Methodsmentioning

confidence: 99%

“…Service and facility decomposition is applied to determine the need of the space. Typically, the area in a public facility is divided to primary, amenity, circulation and technical areas to perform decomposition, while the activities in the facility are characterised by the duration, number of users and area per person [ 48 ]. Spatial use decomposition is applied in this study to determine the functional zones within the co-working space.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Future workspace needs flexibility and diversity: A machine learning-driven behavioural analysis of co-working space

Pan,

Cho,

Sun

et al. 2023

PLoS ONE

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The future of workspace is significantly shaped by the advancements in technologies, changes in work patterns and workers’ desire for an improved well-being. Co-working space is an alternative workspace solution, for cost-effectiveness, the opportunity for diverse and flexible design and multi-use. This study examined the human-centric design choices using spatial and temporal variation of occupancy levels and user behaviour in a flexible co-working space in London. Through a machine-learning-driven analysis, we investigated the time-dependent patterns, decompose space usage, calculate seat utilisation and identify spatial hotspots. The analysis incorporated a large dataset of sensor-detected occupancy data spanning 477 days, comprising more than 140 million (145×106) data points. Additionally, on-site observations of activities were recorded for 13 days spanning over a year, with 110 time instances including more than 1000 snapshots of occupants’ activities, indoor environment, working behaviour and preferences. Results showed that the shared working areas positioned near windows or in more open, connected and visible locations are significantly preferred and utilised for communication and working, and semi-enclosed space on the side with less visibility and higher privacy are preferred for focused working. The flexibility of multi-use opportunity was the most preferred feature for hybrid working. The findings offer data-driven insights for human-centric space planning and design of office spaces in the future, particularly in the context of hybrid working setups, hot-desking and co-working systems.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Future workspace needs flexibility and diversity: A machine learning-driven behavioural analysis of co-working space

Pan,

Cho,

Sun

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

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“…One of the main objectives of urban planning and urban design is forecasting the need for and constructing public facilities and services such as schools, health centres, sports fields, libraries and administrative buildings (Evans, 2009; Johnston, 1977; Kallus, 2010; Lea, 1979), all of which fulfil a very specific function: that is, meeting a community’s specific basic needs (Lee and Lee, 2014; Sanders, 1984). As such, the existence of an optimal number of public facilities in a city is related to a better quality of life and equity (Rusek et al., 2018; Sakashita, 1987; Taleai et al., 2014) and represents benefits for local governments in terms of efficiency and quality of urban design (Mehta, 2013; Zolnik et al., 2010).…”

Section: Facilities and Services In Urban Public Spaces: An Overviewmentioning

confidence: 99%

Estimating public space metrics from nineteenth-century urban cartography: Barcelona’s Cerdà Plan of urban expansion

Riu

Donada

Fortuny

et al. 2021

Environment and Planning B: Urban Analytics and City Science

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Urban cartography enables us to trace the historical and spatial evolution of human settlements, but it also furnishes us with the opportunity to obtain and analyse urban data from the perspective of the present day. Urban plans drafted for the reform and expansion of a city can provide us with valuable urban information about the planned use of new public space. In Western Europe, the historical cartography of Barcelona (Spain) maps the city’s mid-nineteenth century urban expansion project designed to fulfil egalitarian, social and hygienist goals. Here, using geographic information system tools, we digitize Barcelona’s cartography so as to create an urban dataset based on the city’s urban plans – the Cerdà Plans (1859 and 1863) – and to estimate its public space typology. Social centres, hospitals, green spaces, residential areas and communication infrastructures are identified and metrised, and urban public open spaces are analysed using various urban indicators. The urban data thus obtained represent a notable advance on attempts to quantify Cerdà’s original project. The importance attached to public space (>75%) and to both communication infrastructure and urban public open spaces is indicative of the desire to create a new city and to break with the values of old Barcelona. In short, the data obtained serve to undertake a detailed comparison with the present-day reality of Barcelona.

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“…Space utilization may be assessed by the amount of time the accommodations are in active use, by the number of people who use the area, or by a combined measure that reflects the organization’s priorities (Aronoff and Kaplan, 1995). The UK National Audit Office proposed a way to quantify the space utilization rate for education buildings in 1996 (NAO, 1996; Rusek et al , 2018). The utilization rate can be expressed as follows (NAO, 1996; Space Management Group, 2006): …”

Section: Introductionmentioning

confidence: 99%

A change in granularity: measure space utilization through smart technologies

Tagliaro

Zhou

Hua

2020

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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.

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A comparison study on space-use analysis techniques and proposal of a novel method for determining space needs in public facilities

Cited by 8 publications

References 16 publications

Future workspace needs flexibility and diversity: A machine learning-driven behavioural analysis of co-working space

Future workspace needs flexibility and diversity: A machine learning-driven behavioural analysis of co-working space

Estimating public space metrics from nineteenth-century urban cartography: Barcelona’s Cerdà Plan of urban expansion

A change in granularity: measure space utilization through smart technologies

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