Skip to main content
main-content
Top

Hint

Swipe to navigate through the articles of this issue

Published in: SICS Software-Intensive Cyber-Physical Systems 1-2/2018

30-08-2017 | Special Issue Paper

Exploring zero-training algorithms for occupancy detection based on smart meter measurements

Authors: Vincent Becker, Wilhelm Kleiminger

Published in: SICS Software-Intensive Cyber-Physical Systems | Issue 1-2/2018

Login to get access
share
SHARE

Abstract

Detecting the occupancy in households is becoming increasingly important for enabling context-aware applications in smart homes. For example, smart heating systems, which aim at optimising the heating energy, often use the occupancy to determine when to heat the home. The occupancy schedule of a household can be inferred from the electricity consumption, as its changes indicate the presence or absence of inhabitants. As smart meters become more widespread, the real-time electricity consumption of households is often available in digital form. For such data, supervised classifiers are typically employed as occupancy detection mechanisms. However, these have to be trained on data labelled with the occupancy ground truth. Labelling occupancy data requires a high effort, sometimes it even may be impossible, making it difficult to apply these methods in real-world settings. Alternatively, one could use unsupervised classifiers, which do not require any labelled data for training. In this work, we introduce and explain several unsupervised occupancy detection algorithms. We evaluate these algorithms by applying them to three publicly available datasets with ground truth occupancy data, and compare them to one existing unsupervised classifier and several supervised classifiers. Two unsupervised algorithms perform the best and we find that the unsupervised classifiers outperform the supervised ones we compared to. Interestingly, we achieve a similar classification performance on coarse-grained aggregated datasets and their fine-grained counterparts.
Appendix
Available only for authorised users
Literature
1.
go back to reference Akbar A, Nati M, Carrez F, Moessner K (2015) Contextual occupancy detection for smart office by pattern recognition of electricity consumption data. In: 2015 IEEE international conference on communications (ICC), pp 561–566. doi: 10.​1109/​ICC.​2015.​7248381 Akbar A, Nati M, Carrez F, Moessner K (2015) Contextual occupancy detection for smart office by pattern recognition of electricity consumption data. In: 2015 IEEE international conference on communications (ICC), pp 561–566. doi: 10.​1109/​ICC.​2015.​7248381
2.
go back to reference Alhamoud A, Xu P, Englert F, Reinhardt A, Scholl P, Boehnstedt D, Steinmetz R (2015) Extracting human behavior patterns from appliance-level power consumption data. In: Proceedings of the 12th European conference on wireless sensor networks, EWSN 2015, Porto, Portugal, pp 52–67. doi: 10.​1007/​978-3-319-15582-1_​4 Alhamoud A, Xu P, Englert F, Reinhardt A, Scholl P, Boehnstedt D, Steinmetz R (2015) Extracting human behavior patterns from appliance-level power consumption data. In: Proceedings of the 12th European conference on wireless sensor networks, EWSN 2015, Porto, Portugal, pp 52–67. doi: 10.​1007/​978-3-319-15582-1_​4
4.
go back to reference Ardakanian O, Bhattacharya A, Culler D (2016) Non-intrusive techniques for establishing occupancy related energy savings in commercial buildings. In: Proceedings of the 3rd ACM international conference on systems for energy-efficient built environments, buildSys ’16, pp 21–30. doi: 10.​1145/​2993422.​2993574 Ardakanian O, Bhattacharya A, Culler D (2016) Non-intrusive techniques for establishing occupancy related energy savings in commercial buildings. In: Proceedings of the 3rd ACM international conference on systems for energy-efficient built environments, buildSys ’16, pp 21–30. doi: 10.​1145/​2993422.​2993574
5.
go back to reference Barbato A, Borsani L, Capone A, Melzi S (2009) Home energy saving through a user profiling system based on wireless sensors. In: Proceedings of the 1st ACM workshop on embedded sensing systems for energy-efficiency in buildings, buildSys ’09. ACM, New York, NY, USA, pp 49–54. doi: 10.​1145/​1810279.​1810291 Barbato A, Borsani L, Capone A, Melzi S (2009) Home energy saving through a user profiling system based on wireless sensors. In: Proceedings of the 1st ACM workshop on embedded sensing systems for energy-efficiency in buildings, buildSys ’09. ACM, New York, NY, USA, pp 49–54. doi: 10.​1145/​1810279.​1810291
6.
go back to reference Barker S, Mishra A, Irwin D, Cecchet E, Shenoy P, Albrecht J (2012) Smart*: an open data set and tools for enabling research in sustainable homes. In: Proceedings of the 2012 workshop on data mining applications in sustainability (SustKDD 2012), Beijing, China Barker S, Mishra A, Irwin D, Cecchet E, Shenoy P, Albrecht J (2012) Smart*: an open data set and tools for enabling research in sustainable homes. In: Proceedings of the 2012 workshop on data mining applications in sustainability (SustKDD 2012), Beijing, China
7.
go back to reference Beckel C, Kleiminger W, Cicchetti R, Staake T, Santini S (2014) The ECO data set and the performance of non-intrusive load monitoring algorithms. In: Proceedings of the 1st ACM conference on embedded systems for energy-efficient buildings, buildsys ’14. ACM, New York, NY, USA, pp 80–89. doi: 10.​1145/​2674061.​2674064 Beckel C, Kleiminger W, Cicchetti R, Staake T, Santini S (2014) The ECO data set and the performance of non-intrusive load monitoring algorithms. In: Proceedings of the 1st ACM conference on embedded systems for energy-efficient buildings, buildsys ’14. ACM, New York, NY, USA, pp 80–89. doi: 10.​1145/​2674061.​2674064
9.
go back to reference Brackney LJ, Florita AR, Swindler AC, Polese LG, Brunemann GA (2012) Design and performance of an image processing occupancy sensor. In: The second international conference on building energy and environment 2012, Boulder, Colorado, USA, pp 987–994 Brackney LJ, Florita AR, Swindler AC, Polese LG, Brunemann GA (2012) Design and performance of an image processing occupancy sensor. In: The second international conference on building energy and environment 2012, Boulder, Colorado, USA, pp 987–994
14.
go back to reference Chen D, Barker S, Subbaswamy A, Irwin D, Shenoy P (2013) Non-intrusive occupancy monitoring using smart meters. In: Proceedings of the 5th ACM workshop on embedded systems for energy-efficient buildings, buildsys’13. ACM, New York, NY, USA, pp 9:1–9:8. doi: 10.​1145/​2528282.​2528294 Chen D, Barker S, Subbaswamy A, Irwin D, Shenoy P (2013) Non-intrusive occupancy monitoring using smart meters. In: Proceedings of the 5th ACM workshop on embedded systems for energy-efficient buildings, buildsys’13. ACM, New York, NY, USA, pp 9:1–9:8. doi: 10.​1145/​2528282.​2528294
15.
go back to reference Ebadat A, Bottegal G, Molinari M, Varagnolo D, Wahlberg B, Hjalmarsson H, Johansson KH (2015) Multi-room occupancy estimation through adaptive gray-box models. In: Proceedings of the 4th IEEE conference on decision and control (CDC), pp 3705–3711. doi: 10.​1109/​CDC.​2015.​7402794 Ebadat A, Bottegal G, Molinari M, Varagnolo D, Wahlberg B, Hjalmarsson H, Johansson KH (2015) Multi-room occupancy estimation through adaptive gray-box models. In: Proceedings of the 4th IEEE conference on decision and control (CDC), pp 3705–3711. doi: 10.​1109/​CDC.​2015.​7402794
16.
go back to reference Ebadat A, Bottegal G, Varagnolo D, Wahlberg B, Hjalmarsson H, Johansson KH (2015) Blind identification strategies for room occupancy estimation. In: 2015 European control conference (ECC), pp 1315–1320. doi: 10.​1109/​ECC.​2015.​7330720 Ebadat A, Bottegal G, Varagnolo D, Wahlberg B, Hjalmarsson H, Johansson KH (2015) Blind identification strategies for room occupancy estimation. In: 2015 European control conference (ECC), pp 1315–1320. doi: 10.​1109/​ECC.​2015.​7330720
19.
go back to reference Froehlich J, Larson EC, Campbell T, Haggerty C, Fogarty J, Patel SN (2009) Hydrosense: infrastructure-mediated single-point sensing of whole-home water activity. In: Proceedings of the 11th international conference on Ubiquitous computing, UbiComp 2009, Orlando, Florida, USA, pp 235–244. doi: 10.​1145/​1620545.​1620581 Froehlich J, Larson EC, Campbell T, Haggerty C, Fogarty J, Patel SN (2009) Hydrosense: infrastructure-mediated single-point sensing of whole-home water activity. In: Proceedings of the 11th international conference on Ubiquitous computing, UbiComp 2009, Orlando, Florida, USA, pp 235–244. doi: 10.​1145/​1620545.​1620581
20.
go back to reference Gao G, Whitehouse K (2009) The self-programming thermostat: optimizing setback schedules based on home occupancy patterns. In: Proceedings of the 1st ACM workshop on embedded sensing systems for energy-efficiency in buildings, buildSys ’09. ACM, New York, NY, USA, pp 67–72. doi: 10.​1145/​1810279.​1810294 Gao G, Whitehouse K (2009) The self-programming thermostat: optimizing setback schedules based on home occupancy patterns. In: Proceedings of the 1st ACM workshop on embedded sensing systems for energy-efficiency in buildings, buildSys ’09. ACM, New York, NY, USA, pp 67–72. doi: 10.​1145/​1810279.​1810294
22.
go back to reference Gupta M, Intille SS, Larson K (2009) Adding GPS-control to traditional thermostats: an exploration of potential energy savings and design challenges. In: Proceedings of the 7th international conference on pervasive computing, pervasive 2009, Nara, Japan, pp 95–114. doi: 10.​1007/​978-3-642-01516-8_​8 Gupta M, Intille SS, Larson K (2009) Adding GPS-control to traditional thermostats: an exploration of potential energy savings and design challenges. In: Proceedings of the 7th international conference on pervasive computing, pervasive 2009, Nara, Japan, pp 95–114. doi: 10.​1007/​978-3-642-01516-8_​8
24.
go back to reference Jin M, Jia R, Kang Z, Konstantakopoulos IC, Spanos CJ (2014) PresenceSense: zero-training algorithm for individual presence detection based on power monitoring. In: Proceedings of the 1st ACM conference on embedded systems for energy-efficient buildings, buildsys ’14. ACM, New York, NY, USA, pp 1–10. doi: 10.​1145/​2674061.​2674073 Jin M, Jia R, Kang Z, Konstantakopoulos IC, Spanos CJ (2014) PresenceSense: zero-training algorithm for individual presence detection based on power monitoring. In: Proceedings of the 1st ACM conference on embedded systems for energy-efficient buildings, buildsys ’14. ACM, New York, NY, USA, pp 1–10. doi: 10.​1145/​2674061.​2674073
26.
go back to reference Kleiminger W, Beckel C, Dey AK, Santini S (2013) Using unlabeled Wi-Fi scan data to discover occupancy patterns of private households. In: Proceedings of the 11th ACM conference on embedded network sensor systems, sensys ’13, Rome, Italy, pp 47:1–47:2. doi: 10.​1145/​2517351.​2517421 Kleiminger W, Beckel C, Dey AK, Santini S (2013) Using unlabeled Wi-Fi scan data to discover occupancy patterns of private households. In: Proceedings of the 11th ACM conference on embedded network sensor systems, sensys ’13, Rome, Italy, pp 47:1–47:2. doi: 10.​1145/​2517351.​2517421
27.
go back to reference Kleiminger W, Beckel C, Santini S (2015) Household occupancy monitoring using electricity meters. In: Proceedings of the 2015 ACM international joint conference on pervasive and Ubiquitous computing, UbiComp ’15, pp 975–986. doi: 10.​1145/​2750858.​2807538 Kleiminger W, Beckel C, Santini S (2015) Household occupancy monitoring using electricity meters. In: Proceedings of the 2015 ACM international joint conference on pervasive and Ubiquitous computing, UbiComp ’15, pp 975–986. doi: 10.​1145/​2750858.​2807538
28.
go back to reference Kleiminger W, Beckel C, Staake T, Santini S (2013) Occupancy detection from electricity consumption data. In: Proceedings of the 5th ACM workshop on embedded systems for energy-efficient buildings, buildsys’13. ACM, New York, NY, USA, pp 10:1–10:8. doi: 10.​1145/​2528282.​2528295 Kleiminger W, Beckel C, Staake T, Santini S (2013) Occupancy detection from electricity consumption data. In: Proceedings of the 5th ACM workshop on embedded systems for energy-efficient buildings, buildsys’13. ACM, New York, NY, USA, pp 10:1–10:8. doi: 10.​1145/​2528282.​2528295
30.
go back to reference Krumm J, Brush AJB (2011) Learning time-based presence probabilities. In: Proceedings of the 9th international conference on pervasive computing, pervasive 2011, San Francisco, CA, USA, pp 79–96. doi: 10.​1007/​978-3-642-21726-5_​6 Krumm J, Brush AJB (2011) Learning time-based presence probabilities. In: Proceedings of the 9th international conference on pervasive computing, pervasive 2011, San Francisco, CA, USA, pp 79–96. doi: 10.​1007/​978-3-642-21726-5_​6
31.
go back to reference Lu J, Sookoor T, Srinivasan V, Gao G, Holben B, Stankovic J, Field E, Whitehouse K (2010) The smart thermostat: using occupancy sensors to save energy in homes. In: Proceedings of the 8th ACM conference on embedded networked sensor systems, sensys ’10. ACM, New York, NY, USA, pp 211–224. doi: 10.​1145/​1869983.​1870005 Lu J, Sookoor T, Srinivasan V, Gao G, Holben B, Stankovic J, Field E, Whitehouse K (2010) The smart thermostat: using occupancy sensors to save energy in homes. In: Proceedings of the 8th ACM conference on embedded networked sensor systems, sensys ’10. ACM, New York, NY, USA, pp 211–224. doi: 10.​1145/​1869983.​1870005
33.
go back to reference Mozer M, Vidmar L, Dodier RH (1996) The neurothermostat: predictive optimal control of residential heating systems. In: Advances in neural information processing systems, vol 9, NIPS, Denver, CO, USA, pp 953–959 Mozer M, Vidmar L, Dodier RH (1996) The neurothermostat: predictive optimal control of residential heating systems. In: Advances in neural information processing systems, vol 9, NIPS, Denver, CO, USA, pp 953–959
35.
go back to reference Patel SN, Reynolds MS, Abowd GD (2008) Detecting human movement by differential air pressure sensing in HVAC system ductwork: an exploration in infrastructure mediated sensing. In: Proceedings of the 6th international conference on pervasive computing, pervasive ’08, pp 1–18. doi: 10.​1007/​978-3-540-79576-6_​1 Patel SN, Reynolds MS, Abowd GD (2008) Detecting human movement by differential air pressure sensing in HVAC system ductwork: an exploration in infrastructure mediated sensing. In: Proceedings of the 6th international conference on pervasive computing, pervasive ’08, pp 1–18. doi: 10.​1007/​978-3-540-79576-6_​1
36.
go back to reference Patel SN, Robertson T, Kientz JA, Reynolds MS, Abowd GD (2007) At the flick of a switch: detecting and classifying unique electrical events on the residential power line. In: Proceedings of the 9th international conference on Ubiquitous computing, UbiComp ’07, Innsbruck, Austria, pp 271–288. doi: 10.​1007/​978-3-540-74853-3_​16 Patel SN, Robertson T, Kientz JA, Reynolds MS, Abowd GD (2007) At the flick of a switch: detecting and classifying unique electrical events on the residential power line. In: Proceedings of the 9th international conference on Ubiquitous computing, UbiComp ’07, Innsbruck, Austria, pp 271–288. doi: 10.​1007/​978-3-540-74853-3_​16
39.
go back to reference Scott J, Bernheim Brush A, Krumm J, Meyers B, Hazas M, Hodges S, Villar N (2011) Preheat: controlling home heating using occupancy prediction. In: Proceedings of the 13th international conference on Ubiquitous computing, UbiComp ’11. ACM, New York, NY, USA, pp 281–290. doi: 10.​1145/​2030112.​2030151 Scott J, Bernheim Brush A, Krumm J, Meyers B, Hazas M, Hodges S, Villar N (2011) Preheat: controlling home heating using occupancy prediction. In: Proceedings of the 13th international conference on Ubiquitous computing, UbiComp ’11. ACM, New York, NY, USA, pp 281–290. doi: 10.​1145/​2030112.​2030151
41.
go back to reference Soltanaghaei E, Whitehouse K (2016) Walksense: classifying home occupancy states using walkway sensing. In: Proceedings of the 3rd ACM international conference on systems for energy-efficient built environments, buildsys ’16, pp 167–176. doi: 10.​1145/​2993422.​2993576 Soltanaghaei E, Whitehouse K (2016) Walksense: classifying home occupancy states using walkway sensing. In: Proceedings of the 3rd ACM international conference on systems for energy-efficient built environments, buildsys ’16, pp 167–176. doi: 10.​1145/​2993422.​2993576
42.
go back to reference Szczurek A, Maciejewska M (2016) Detection of occupancy events from indoor air monitoring data. In: 3rd international conference on mathematics and computers in sciences and in industry (MCSI), pp 229–234. doi: 10.​1109/​MCSI.​2016.​050 Szczurek A, Maciejewska M (2016) Detection of occupancy events from indoor air monitoring data. In: 3rd international conference on mathematics and computers in sciences and in industry (MCSI), pp 229–234. doi: 10.​1109/​MCSI.​2016.​050
43.
go back to reference Tang G, Wu K, Lei J, Xiao W (2015) The meter tells you are at home! Non-intrusive occupancy detection via load curve data. In: 2015 IEEE international conference on smart grid communications (Smartgridcomm), Miami, FL, USA, pp 897–902. doi: 10.​1109/​SmartGridComm.​2015.​7436415 Tang G, Wu K, Lei J, Xiao W (2015) The meter tells you are at home! Non-intrusive occupancy detection via load curve data. In: 2015 IEEE international conference on smart grid communications (Smartgridcomm), Miami, FL, USA, pp 897–902. doi: 10.​1109/​SmartGridComm.​2015.​7436415
44.
go back to reference Tapia EM, Intille SS, Larson K (2004) Activity recognition in the home using simple and ubiquitous sensors. In: Proceedings of the 2nd international conference on pervasive computing, pervasive ’04, Vienna, Austria, pp 158–175. doi: 10.​1007/​978-3-540-24646-6_​10 Tapia EM, Intille SS, Larson K (2004) Activity recognition in the home using simple and ubiquitous sensors. In: Proceedings of the 2nd international conference on pervasive computing, pervasive ’04, Vienna, Austria, pp 158–175. doi: 10.​1007/​978-3-540-24646-6_​10
47.
go back to reference van Kasteren T, Noulas AK, Englebienne G, Kröse BJA (2008) Accurate activity recognition in a home setting. In: Proceedings of the 10th international conference on Ubiquitous computing, UbiComp 2008, Seoul, Korea, pp 1–9. doi: 10.​1145/​1409635.​1409637 van Kasteren T, Noulas AK, Englebienne G, Kröse BJA (2008) Accurate activity recognition in a home setting. In: Proceedings of the 10th international conference on Ubiquitous computing, UbiComp 2008, Seoul, Korea, pp 1–9. doi: 10.​1145/​1409635.​1409637
50.
go back to reference Woodstock TK, Radke RJ, Sanderson AC (2016) Sensor fusion for occupancy detection and activity recognition using time-of-flight sensors. In: Proceedings of the 19th international conference on information fusion (FUSION), pp 1695–1701 Woodstock TK, Radke RJ, Sanderson AC (2016) Sensor fusion for occupancy detection and activity recognition using time-of-flight sensors. In: Proceedings of the 19th international conference on information fusion (FUSION), pp 1695–1701
51.
go back to reference Yang L, Ting K, Srivastava MB (2014) Inferring occupancy from opportunistically available sensor data. In: Proceedings of the IEEE international conference on pervasive computing and communications, PerCom 2014, Los Alamitos, CA, USA, pp 60–68. doi: 10.​1109/​PerCom.​2014.​6813945 Yang L, Ting K, Srivastava MB (2014) Inferring occupancy from opportunistically available sensor data. In: Proceedings of the IEEE international conference on pervasive computing and communications, PerCom 2014, Los Alamitos, CA, USA, pp 60–68. doi: 10.​1109/​PerCom.​2014.​6813945
Metadata
Title
Exploring zero-training algorithms for occupancy detection based on smart meter measurements
Authors
Vincent Becker
Wilhelm Kleiminger
Publication date
30-08-2017
Publisher
Springer Berlin Heidelberg
Published in
SICS Software-Intensive Cyber-Physical Systems / Issue 1-2/2018
Print ISSN: 2524-8510
Electronic ISSN: 2524-8529
DOI
https://doi.org/10.1007/s00450-017-0344-9

Other articles of this Issue 1-2/2018

SICS Software-Intensive Cyber-Physical Systems 1-2/2018 Go to the issue

Premium Partner