Modeling Context Information in Pervasive Computing Systems
Pervasive '02 Proceedings of the First International Conference on Pervasive Computing
Location Aware Resource Management in Smart Homes
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Context-Aware Resource Management in Multi-Inhabitant Smart Homes: A Nash H-Learning based Approach
PERCOM '06 Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications
An Integrated Architecture for Demand Response Communications and Control
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
An Autonomic Context Management System for Pervasive Computing
PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
Human-Computer Interaction
Mobile Data Mining for Intelligent Healthcare Support
HICSS '09 Proceedings of the 42nd Hawaii International Conference on System Sciences
iPower: an energy conservation system for intelligent buildings by wireless sensor networks
International Journal of Sensor Networks
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Building Automation Simulator and Control Strategy for Intelligent and Energy Efficient Home
EMS '09 Proceedings of the 2009 Third UKSim European Symposium on Computer Modeling and Simulation
Inferring Personal Information from Demand-Response Systems
IEEE Security and Privacy
Bathroom activity monitoring based on sound
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Simultaneous tracking and activity recognition (STAR) using many anonymous, binary sensors
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
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Recently due to major changes in the structure of electricity industry and the rising costs of power generation, many countries have realized the potential and benefits of smart metering systems and demand response programs in balancing between the supply and the demand. DR mechanisms are capable of controlling the user energy consumption according to load conditions and providing effective energy management. However, they are typically performed regardless of user's situation and current activities. Factoring in the user's contextual information which is relevant to their current or future energy consumption can significantly increase the effectiveness of DR programs and enable adaptive and personalized execution of DR control actions. In this paper, we review current DR techniques and discuss the state-of the-art smart energy management approaches that take into account contextual information. An overview of context reasoning and learning techniques for smart homes are presented to demonstrate how knowledge of user activities can be utilized in context-aware DR mechanisms. Our aim is to provide a better understanding of DR programs and highlight the importance of the contextawareness in improving smart energy management.