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In ubiquitous sensor networks (USN), sensor node localization is normally performed with global positioning system (GPS) or radio signal strength (RSS) between a target node and reference nodes. Because GPS is not available in indoor environments, RSS-based approach is commonly used for indoor localization. However, RSS-based approach is hard to be applied to real indoor environments (e.g., home) because of signal interferences with various indoor obstacles such as walls, doors, furniture, and electric appliances. In this paper, we propose an efficient indoor localization method for Zigbee sensor nodes by classifying link quality indicator (LQI) patterns between a target node and multiple reference nodes rather than using calculation with RSS values. And we also present the results of indoor localization experiments in our ubiquitous home network test bed using the proposed localization method.

Uncontrolled fires occurring in wild areas cause significant damage to natural and human resources. Many countries are looking for ways to fight forest fires at an early stage using sensor networks, by integrating IT technologies. Studies in the fire-related sensor network field are broadly classified into efficient processing of fire data on sensor nodes and energy efficiency during communications among wireless sensor nodes in case of fire. Most studies of sensor network energy efficiency so far mainly focus on extending the connectivity of the entire network and minimizing isolated nodes by applying power evenly to each sensor node through efficient cluster-based routing. This paper proposes an energy-efficient fire monitoring protocol over cluster-based sensor networks. The proposed protocol dynamically creates and reorganizes the sensor network cluster hierarchy according to the direction of fire propagation over the sensor network clusters. This paper also presents experimental results to show that the proposed protocol is more energy efficient than fire monitoring with existing cluster-based sensor network protocols.