TY - GEN
T1 - An Intelligent Hot-Desking Model Based on Occupancy Sensor Data and Its Potential for Social Impact
AU - Maraslis, Konstantinos
AU - Cooper, Peter
AU - Tryfonas, Theo
AU - Oikonomou, George
PY - 2016/9/4
Y1 - 2016/9/4
N2 - 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.
AB - 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.
KW - Hot-desking
KW - Optimisation
UR - http://www.scopus.com/inward/record.url?scp=84988602729&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-53416-8_9
DO - 10.1007/978-3-662-53416-8_9
M3 - Conference Contribution (Conference Proceeding)
AN - SCOPUS:84988602729
SN - 9783662534151
VL - 9860 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 142
EP - 158
BT - Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVII
PB - Springer-Verlag Berlin
T2 - 49th Hawaii International Conference on System Sciences, HICSS 2016
Y2 - 5 January 2016 through 8 January 2016
ER -