Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Learning and inferring transportation routines
Artificial Intelligence
Global indoor self-localization based on the ambient magnetic field
Robotics and Autonomous Systems
MagiTact: interaction with mobile devices based on compass (magnetic) sensor
Proceedings of the 15th international conference on Intelligent user interfaces
Proceedings of the 12th ACM international conference on Ubiquitous computing
Using wearable activity type detection to improve physical activity energy expenditure estimation
Proceedings of the 12th ACM international conference on Ubiquitous computing
Ubiquitous mobile instrumentation
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
MagnetiCode: physical mobile interaction through time-encoded magnetic identification tags
Proceedings of the 8th International Conference on Tangible, Embedded and Embodied Interaction
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Human activity recognition and human behavior understanding play a central role in the field of ubiquitous computing. In this paper, we propose a novel method using magnetometer embedded in the mobile phone to recognize activities by detecting household appliance usage. The key idea of our approach is that when the mobile phone user performs a certain activity at home, the embedded magnetometer is capable of capturing the changes of the magnetic field strength around the mobile phone caused by the household appliance in operation. Our mobile application uses these changes as magnetic signatures for each of these appliance such that the daily household acitivities associated with these appliance such as cooking can be recognized.