TY - GEN
T1 - Profiling spatial and temporal behaviour in sensor networks
T2 - 9th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, IEEE ISSNIP 2014
AU - Rashidi, Lida
AU - Rajasegarar, Sutharshan
AU - Leckie, Christopher
AU - Nati, Michele
AU - Gluhak, Alexander
AU - Imran, Muhammad Ali
AU - Palaniswami, Marimuthu
PY - 2014
Y1 - 2014
N2 - Wireless sensor networks (WSNs) provide a cost-effective platform for monitoring phenomena of interest at fine spatial and temporal resolutions. In this paper, we consider the application of monitoring power usage in an office environment at the resolution of individual users. A key challenge in this context is how to extract meaningful profiles of user behaviour in the large volume of monitoring data collected by the WSN. To manage the complexity of learning such profiles in this context, we propose a query based model for profiling. This query based model provides the ability to characterize the spatial and temporal occurrences of the power usage patterns of interest. We demonstrate the effectiveness of our query-based profiling model for finding relevant electricity usage patterns in a real life data set of power measurements collected by a WSN deployment in an office environment. To the best of our knowledge, this is the first time such a case study has been made on analysing the power usage of users at such a fine scale in an office environment.
AB - Wireless sensor networks (WSNs) provide a cost-effective platform for monitoring phenomena of interest at fine spatial and temporal resolutions. In this paper, we consider the application of monitoring power usage in an office environment at the resolution of individual users. A key challenge in this context is how to extract meaningful profiles of user behaviour in the large volume of monitoring data collected by the WSN. To manage the complexity of learning such profiles in this context, we propose a query based model for profiling. This query based model provides the ability to characterize the spatial and temporal occurrences of the power usage patterns of interest. We demonstrate the effectiveness of our query-based profiling model for finding relevant electricity usage patterns in a real life data set of power measurements collected by a WSN deployment in an office environment. To the best of our knowledge, this is the first time such a case study has been made on analysing the power usage of users at such a fine scale in an office environment.
UR - https://www.scopus.com/pages/publications/84903742312
U2 - 10.1109/ISSNIP.2014.6827606
DO - 10.1109/ISSNIP.2014.6827606
M3 - Conference contribution
AN - SCOPUS:84903742312
SN - 9781479928439
T3 - IEEE ISSNIP 2014 - 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Conference Proceedings
BT - IEEE ISSNIP 2014 - 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Conference Proceedings
PB - IEEE Computer Society
Y2 - 21 April 2014 through 24 April 2014
ER -