Task phase recognition and task progress estimation for highly mobile workers in large building complexes

Stisen, Allan; Blunck, Henrik; Kjærgaard, Mikkel Baun; Prentow, Thor Siiger; Mathisen, Andreas; Sørensen, Søren Krogh; Grønbæk, Kaj

doi:10.1016/j.pmcj.2016.08.016

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…Literature shows that IoT applications are applied to a wide range of built environments. Although our focus was mostly on academic buildings and offices, the studied literature also covers hospitals Ruiz-Ruiz et al, 2014;Stisen et al, 2017), outdoor settings (Abedi et al, 2013;Chang et al, 2010;Versichele et al, 2012), sports venues (Liebig et al, 2014;Stange et al, 2011), residential buildings (Chuah et al, 2013;Pesic et al, 2019;Villarrubia et al, 2014), train stations (Daamen et al, 2015;van den Heuvel & Hoogenraad, 2014), and airports (Schauer et al, 2014). The literature has been categorized by type of application.…”

Section: Literature Studymentioning

confidence: 99%

Towards a smart campus: supporting campus decisions with Internet of Things applications

Valks

Arkesteijn

Koutamanis

et al. 2020

Building Research & Information

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At universities worldwide, creating a 'smart campus' is gaining significance. This is a response to the increasingly dynamic use of the campus and the pressure on resources: energy, financial and human resources. The university community has become more mobile, student numbers more unpredictable and funding more uncertain. Consequently, campus strategies focus on resource efficiency and sharing space, requiring investment in management information to improve decision making. The Internet of Things (IoT) can help to provide big data about use patterns: by collecting real-time data on space utilization, users can make better use of current spaces and real estate managers can make better decisions about long-term demand. Furthermore, space utilisation data can be complemented with user feedback data and environmental variables, e.g. noise levels, luminance. In this research we identify the capabilities of existing IoT applications through a literature study. Literature also suggests that information from IoT applications is not utilized in organisational decision-making processes. Through four case studies we analyse these decision-making processes and identify the process-level requirements to make strategic decisions in campus management. Then we show how information from the IoT can be directly connected to these processes, thus providing a valuable addition of real-time data as input.

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Section: Literature Studymentioning

confidence: 99%

Towards a smart campus: supporting campus decisions with Internet of Things applications

Valks

Arkesteijn

Koutamanis

et al. 2020

Building Research & Information

View full text Add to dashboard Cite

show abstract

“…The discovery of contextual information from daily routines has been previously addressed by [19]. Task phase recognition and progress estimation by modeling highly mobile workers in a large hospital complex was proposed [26]. Here, approximation of localizations from WiFi access points and smartphone accelerometer sensors were used.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Task Recognition: Towards Enabling Productivity Assistance in Daily Life

Liono

Rahaman

Salim

et al. 2020

Proceedings of the 2020 International Conference on Multimedia Retrieval

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We introduce the novel research problem of task recognition in daily life. We recognize tasks such as project management, planning, meal-breaks, communication, documentation, and family care. We capture Cyber, Physical, and Social (CSP) activities of 17 participants over four weeks using device-based sensing, app activity logging, and an experience sampling methodology. Our cohort includes students, casual workers, and professionals, forming the first realworld context-rich task behaviour dataset. We model CPS activities across different task categories, results highlight the importance of considering the CPS feature sets in modelling, especially workrelated tasks. CCS CONCEPTS• Human-centered computing → Empirical studies in ubiquitous and mobile computing.

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Task phase recognition and task progress estimation for highly mobile workers in large building complexes

Cited by 2 publications

References 24 publications

Towards a smart campus: supporting campus decisions with Internet of Things applications

Towards a smart campus: supporting campus decisions with Internet of Things applications

Intelligent Task Recognition: Towards Enabling Productivity Assistance in Daily Life

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