Collaborative Context Recognition for Handheld Devices
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Exploiting Context-Awareness for the Autonomic Management of Mobile Ad Hoc Networks
Journal of Network and Systems Management
Context-Aware Mobile Media and Social Networks
Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services
Environmental sound recognition with time-frequency audio features
IEEE Transactions on Audio, Speech, and Language Processing
Online evolutionary context-aware classifier ensemble framework for object recognition
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
An ontology for mobile device sensor-based context awareness
CONTEXT'03 Proceedings of the 4th international and interdisciplinary conference on Modeling and using context
An analytical model for multi-epidemic information dissemination
Journal of Parallel and Distributed Computing
Integrating collaborative context information with social media: a study of user perceptions
Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration
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Mobile devices, together with their users, are constantly moving from one situation to another. To adapt applications to these changing contexts, the devices must have ways to recognize the contexts. There are various sources for context information: sensors, tags, positioning systems, to name a few. The raw signals from these sources are translated into higher-level interpretations of the situation. Unfortunately, such data is often unreliable and constantly changing. We seek to improve the reliability of context recognition through an analogy to human behavior. Where multiple devices are around, they can jointly negotiate on a suitable context and behave accordingly. This approach is becoming particularly attractive with the multitude of personal devices on the market. We present a collaborative context determination scheme, suggest examples of potential applications of such collaborative behavior, and raise issues of context recognition, context communication, and network requirements.