Abstract
In this paper we propose and implement a battery-shaped sensor node that can monitor the use of an electrical device into which it is inserted by sensing the electrical current passing through the device. We live surrounded by large numbers of electrical devices and frequently use them in our daily lives, and so we can estimate high-level daily activities by recognizing their use. Therefore, many ubiquitous and wearable sensing studies have attempted to recognize the use of electrical devices by attaching sensor nodes to the devices directly or by attaching multiple sensors to a user. With our node, we can easily monitor the use of an electrical device simply by inserting the node into the battery case of the device. We also propose a method that automatically identifies into which electrical device the sensor node is inserted and recognizes electrical events related to the device by analyzing the current sensor data. We evaluated our method by using sensor data obtained from three real houses and achieved very high identification and recognition accuracies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Mynatt, E., Rowan, J., Craighill, S., Jacobs, A.: Digital family portraits: Supporting peace of mind for extended family members. In: CHI 2001, pp. 333–340 (2001)
Maekawa, T., Yanagisawa, Y., Kishino, Y., Kamei, K., Sakurai, Y., Okadome, T.: Object-blog system for environment-generated content. IEEE Pervasive Computing 7(4), 20–27 (2008)
Lukowicz, P., Junker, H., Stäger, M., von Büren, T., Tröster, G.: WearNET: A Distributed Multi-sensor System for Context Aware Wearables. In: Borriello, G., Holmquist, L.E. (eds.) UbiComp 2002. LNCS, vol. 2498, pp. 361–370. Springer, Heidelberg (2002)
Bao, L., Intille, S.S.: Activity Recognition from User-Annotated Acceleration Data. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 1–17. Springer, Heidelberg (2004)
Maekawa, T., Watanabe, S.: Unsupervised activity recognition with user’s physical characteristics data. In: Int’l Symp. on Wearable Computers, pp. 89–96 (2011)
Philipose, M., Fishkin, K., Perkowitz, M.: Inferring activities from interactions with objects. IEEE Pervasive Computing 3(4), 50–57 (2004)
Tapia, E.M., Intille, S.S., Larson, K.: Portable Wireless Sensors for Object Usage Sensing in the Home: Challenges and Practicalities. In: Schiele, B., Dey, A.K., Gellersen, H., de Ruyter, B., Tscheligi, M., Wichert, R., Aarts, E., Buchmann, A. (eds.) AmI 2007. LNCS, vol. 4794, pp. 19–37. Springer, Heidelberg (2007)
van Kasteren, T., Noulas, A., Englebienne, G., Kröse, B.: Accurate activity recognition in a home setting. In: Ubicomp 2008, pp. 1–9 (2008)
Beckmann, C., Consolvo, S., LaMarca, A.: Some Assembly Required: Supporting End-User Sensor Installation in Domestic Ubiquitous Computing Environments. In: Davies, N., Mynatt, E.D., Siio, I. (eds.) UbiComp 2004. LNCS, vol. 3205, pp. 107–124. Springer, Heidelberg (2004)
Tapia, E.M., Intille, S.S., Larson, K.: Activity Recognition in the Home Using Simple and Ubiquitous Sensors. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 158–175. Springer, Heidelberg (2004)
Kim, Y., Schmid, T., Charbiwala, Z., Srivastava, M.: ViridiScope: design and implementation of a fine grained power monitoring system for homes. In: Ubicomp 2009, pp. 245–254 (2009)
Cohn, G., Gupta, S., Froehlich, J., Larson, E., Patel, S.N.: GasSense: Appliance-Level, Single-Point Sensing of Gas Activity in the Home. In: Floréen, P., Krüger, A., Spasojevic, M. (eds.) Pervasive 2010. LNCS, vol. 6030, pp. 265–282. Springer, Heidelberg (2010)
Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., Patel, S.: Hydrosense: Infrastructure-mediated single-point sensing of whole-home water activity. In: Ubicomp 2009, pp. 235–244 (2009)
Patel, S.N., Robertson, T., Kientz, J.A., Reynolds, M.S., Abowd, G.D.: At the Flick of a Switch: Detecting and Classifying Unique Electrical Events on the Residential Power Line (Nominated for the Best Paper Award). In: Krumm, J., Abowd, G.D., Seneviratne, A., Strang, T. (eds.) UbiComp 2007. LNCS, vol. 4717, pp. 271–288. Springer, Heidelberg (2007)
Gupta, S., Reynolds, M., Patel, S.: ElectriSense: Single-point sensing using EMI for electrical event detection and classification in the home. In: Ubicomp 2010, pp. 139–148 (2010)
Lifton, J., Feldmeier, M., Ono, Y., Lewis, C., Paradiso, J.: A platform for ubiquitous sensor deployment in occupational and domestic environments. In: IPSN 2007, pp. 119–127 (2007)
Jiang, X., Dawson-Haggerty, S., Dutta, P., Culler, D.: Design and implementation of a high-fidelity ac metering network. In: IPSN 2009, pp. 253–264 (2009)
Ravi, N., Dandekar, N., Mysore, P., Littman, M.: Activity recognition from accelerometer data. In: IAAI 2005, vol. 20, pp. 1541–1546 (2005)
Maekawa, T., Yanagisawa, Y., Kishino, Y., Ishiguro, K., Kamei, K., Sakurai, Y., Okadome, T.: Object-Based Activity Recognition with Heterogeneous Sensors on Wrist. In: Floréen, P., Krüger, A., Spasojevic, M. (eds.) Pervasive 2010. LNCS, vol. 6030, pp. 246–264. Springer, Heidelberg (2010)
Maekawa, T., Kishino, Y., Sakurai, Y., Suyama, T.: Recognizing the Use of Portable Electrical Devices with Hand-Worn Magnetic Sensors. In: Lyons, K., Hightower, J., Huang, E.M. (eds.) Pervasive 2011. LNCS, vol. 6696, pp. 276–293. Springer, Heidelberg (2011)
Logan, B., Healey, J., Philipose, M., Tapia, E.M., Intille, S.S.: A Long-Term Evaluation of Sensing Modalities for Activity Recognition. In: Krumm, J., Abowd, G.D., Seneviratne, A., Strang, T. (eds.) UbiComp 2007. LNCS, vol. 4717, pp. 483–500. Springer, Heidelberg (2007)
Rabiner, L.: A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77(2), 257–286 (1989)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Maekawa, T., Kishino, Y., Yanagisawa, Y., Sakurai, Y. (2012). Mimic Sensors: Battery-Shaped Sensor Node for Detecting Electrical Events of Handheld Devices. In: Kay, J., Lukowicz, P., Tokuda, H., Olivier, P., Krüger, A. (eds) Pervasive Computing. Pervasive 2012. Lecture Notes in Computer Science, vol 7319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31205-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-31205-2_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31204-5
Online ISBN: 978-3-642-31205-2
eBook Packages: Computer ScienceComputer Science (R0)