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An Intelligent Hot-Desking Model Based on Occupancy Sensor Data and Its Potential for Social Impact

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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVII

Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 9860))

Abstract

In this paper we develop a model that utilises occupancy sensor data in a commercial Hot-Desking environment. Hot-Desking (or ‘office-hoteling’) is a method of office resource management that emerged in the nineties hoping to reduce the real estate costs of workplaces, by allowing offices to be used interchangeably among employees. We show that sensor data can be used to facilitate office resources management, in our case desk allocation in a Hot-Desking environment, with results that outweigh the costs of occupancy detection. We are able to optimise desk utilisation based on quality occupancy data and also demonstrate the effectiveness of the model by comparing it to a theoretically ideal, but impractical in real life, model. We then explain how a generalisation of the model that includes input from human sensors (e.g. social media) besides the presence sensing and pre-declared personal preferences, can be used, with potential impact on wider community scale.

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Author information

Authors and Affiliations

  1. University of Bristol, Bristol, UK

    Konstantinos Maraslis, Peter Cooper, Theo Tryfonas & George Oikonomou

  2. Arup, London, UK

    Peter Cooper

Authors
  1. Konstantinos Maraslis
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  2. Peter Cooper
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  3. Theo Tryfonas
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  4. George Oikonomou
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Corresponding author

Correspondence to Konstantinos Maraslis .

Editor information

Editors and Affiliations

  1. IRIT, Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  2. FAW, University of Linz, Linz, Austria

    Josef Küng

  3. FAW, University of Linz, Linz, Austria

    Roland Wagner

  4. MIT SENSEable City Lab, Cambridge, Massachusetts, USA

    Amin Anjomshoaa

  5. Faculty of Business and Information Technology, University of Ontario Institute of Technology (UOIT), Oshawa, Ontario, Canada

    Patrick C. K. Hung

  6. Trinity University, Plainview, Texas, USA

    Dominik Kalisch

  7. New York University, Brooklyn, New York, USA

    Stanislav Sobolevsky

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Maraslis, K., Cooper, P., Tryfonas, T., Oikonomou, G. (2016). An Intelligent Hot-Desking Model Based on Occupancy Sensor Data and Its Potential for Social Impact. In: Hameurlain, A., et al. Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVII. Lecture Notes in Computer Science(), vol 9860. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53416-8_9

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  • DOI: https://doi.org/10.1007/978-3-662-53416-8_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-53415-1

  • Online ISBN: 978-3-662-53416-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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