DAFNE: a distributed and adaptive fusion engine
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Multipoint-to-point communications for SHE surveillance with QoS and QoE management
Engineering Applications of Artificial Intelligence
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Every home has its own unique considerations for location-aware applications. This makes a flexible architecture very crucial for efficiently integrating various tracking devices/models for adapting to real human needs. Here, we propose a reciprocal and extensible architecture to flexibly add/remove tracking sensors/models for tracking multiple targets in a smart home. Regarding tracking devices, we employ 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 reciprocal and cooperative interaction among sensors from the two categories. Such reciprocal cooperation aims to increase the accuracy of location estimates and to compensate for the limitations of each sensor or a tracking algorithm, which allows us to track multiple targets simultaneously in a more reliable way. Moreover, the approach demonstrated in this paper can serve as a guideline to help users customize sensor arrangements to fulfill their requirements. Our experimental results, which comprise three tracking scenarios using a load sensory floor as the seamless sensor and RF identifications (RFIDs) as seamful sensors, demonstrate the effectiveness of the proposed architecture.