TY - GEN
T1 - Recognizing energy-related activities using sensors commonly installed in office buildings
AU - Milenkovic, M.
AU - Amft, O.D.
PY - 2013
Y1 - 2013
N2 - Automated control based on user activities and preferences could reduce energy consumption of office buildings. In this paper, we investigated generalisation properties of an office activity recognition approach using sensors that are frequently installed in modern and refurbished office buildings. In particular, per-desk passive infrared (PIR) sensors and power plug meters were considered in an evaluation study including more than 100 hours of data from both, a single-person room and a three-user multi-person office room. Layered hidden Markov models (LHMM) were used for the recognition. Results showed that 30 hours and 50 hours of training data were needed to achieve robust recognition of desk activities and estimate people count, respectively. The recognition can be performed independent of a particular occupant desk. In further simulations considering different energy profiles, we show how energy consumption due to lighting and office appliances is related to occupant behaviour.
AB - Automated control based on user activities and preferences could reduce energy consumption of office buildings. In this paper, we investigated generalisation properties of an office activity recognition approach using sensors that are frequently installed in modern and refurbished office buildings. In particular, per-desk passive infrared (PIR) sensors and power plug meters were considered in an evaluation study including more than 100 hours of data from both, a single-person room and a three-user multi-person office room. Layered hidden Markov models (LHMM) were used for the recognition. Results showed that 30 hours and 50 hours of training data were needed to achieve robust recognition of desk activities and estimate people count, respectively. The recognition can be performed independent of a particular occupant desk. In further simulations considering different energy profiles, we show how energy consumption due to lighting and office appliances is related to occupant behaviour.
U2 - 10.1016/j.procs.2013.06.089
DO - 10.1016/j.procs.2013.06.089
M3 - Conference contribution
T3 - Procedia Computer Science
SP - 669
EP - 677
BT - Proceedings of the 4th International Conference on Ambient Systems, Networks and Technologies (ANT 2013) and the 3rd International Conference on Sustainable Energy Information Technology (SEIT-2013), 25-28 June 2013, Halifax, Canada
PB - Elsevier/Procedia Computer Science
T2 - conference; The 3rd International Conference on Sustainable Energy Information Technology (SEIT '13); 2013-06-25; 2013-06-28
Y2 - 25 June 2013 through 28 June 2013
ER -
