Chih-Yung Chen

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This paper presents a passive auto-focus camera control systemwhich can easily achieve the function of auto-focus with no necessary of any active component (e.g., infrared or ultrasonic sensor) in comparison with the conventional active focus system. To implement the technique we developed, the hardware system including the adjustable lens with CMOS sensor(More)
This paper presents an indoor positioning technique based on neural networks (NN). The received signal strengths (RSS) sensed by Zigbee wireless sensor network were used to estimate the position of object. From the simulation results shown, the NN technique proposed still has the high accuracy even the signal strengths sensed are unstable. Besides, from the(More)
This study develops an intelligent wireless indoor positioning system (IPS), which includes new beam antenna design and modified probabilistic neural network based positioning algorithm. The six directional antennas can obtain the angle between an object and the station. Then, a modified probabilistic neural network is applied to estimate the accurate(More)
This paper presents an indoor positioning technique using a modified probabilistic neural network (MPNN) scheme. It measures the received signal strength (RSS) between an object and stations, and then transforms the RSS into distances. A MPNN engine determines coordinate of the object with the input distances. The experiments are conducted in a realistic(More)
A new smart building evacuation system consisting of intelligent integration supervisory system (IISS), smart emergency indicator boards (SEIB) and fuzzy-based approach for evacuation modeling is presented. In an emergency, the IWSS can obtain the positions of disaster area from wireless sensors. Then, the system determinates safe evacuation routes using a(More)