A passive infrared or pyroelectric infrared (PIR) sensor is mainly used to sense the existence of moving objects in an indoor environment. However, in an outdoor environment, there are often outbreaks of false alarms from environmental changes and other sources. Therefore, it is difficult to provide reliable detection outdoors. In this paper, two algorithms are proposed to reduce false alarms and provide trustworthy quality to surveillance systems. We gather PIR signals outdoors, analyze the collected data, and extract the target features defined as window energy and alarm duration. Using these features, we model target and false alarms, from which we propose two target decision algorithms: window energy detection and alarm duration detection. Simulation results using real PIR signals show the performance of the proposed algorithms.
This paper presents the Ubiquitous Sensor Network (USN) testbed, which is deployed at Electronics and Telecommunications Research Institute (ETRI), in Republic of Korea. USN testbed is a state-of-the-art sensor network experimental facility composed of various components. It includes heterogeneous sensor nodes with variety of sensing module ranging from ultralow power to high performance hardware platforms, a scalable and reliable Ethernet based wired backplane network to program, interact with and receive/send data from/to the sensor nodes, an easily extendable application software suite which glues and drive everything in a user friendly manner, and an indoor and outdoor deployment space offering various environmental characteristics. We also included two case studies where researchers have put USN testbed into practice for experimental evaluation of algorithms and networking protocols. The case studies cover routing and clustering protocol in wireless sensor networks.
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