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Multi-resident activity recognition is among a key enabler in many context-aware applications in a smart home. However, most of prior researches ignore the potential interactions among residents in order to simplify problem complexity. On the other hand, multiple-resident activities are usually recognized using cameras or wearable sensors. However, due to human-centric concerns, it is more preferable...
Every home has its own unique considerations for location-aware applications. This makes a flexible architecture very crucial for efficiently integrating various tracking devices for adapting to real human needs. We employ tracking sensors from two different categories, those with seamless sensors and those with seamful ones. This allows us to take human-centric needs into consideration and to facilitate...
The use of message-oriented architectures in pervasive systems has increased noticeably because of their failure tolerant and loosely-coupled natures. Meanwhile, nondirectory-based service management protocols are believed to be more suitable for small scale pervasive environments such as smart homes. However, the paradigm mismatch causes nondirectory-based protocols suffer from network flooding problems...
Current trends suggest that the smart home systems should be adaptive and robust. Many service-oriented architectures and discovery protocols for the smart home environments have been proposed to support on-line re-composition of home services in reaction to changing environments. Nevertheless, few researches have been done to improve the robustness of smart home systems. This paper attempts to propose...
This paper presents a practical application called "activity map" to serve as guidance to show ambient intelligence-related contextual information gathered from both humans and their surrounding environments. The activity map utilizes results inferred from a location-aware activity recognition approach to statistically show a resident's possibly interleaved activities along with corresponding...
Smart home which understands user's preference and provides right services at right time is the current trend. In this paper, we aim at developing a system which can achieve this objective by using the Bayesian network to model user's preference. Instead of assuming the structure of Bayesian network is invariant, our system interacts with user appropriately to obtain some useful information and we...
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