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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Yeh, Lun-WuSubject: search.filters.subject.pervasive computing

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Now showing 1 - 4 of 4
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    iLamp: A Sensor-Enhanced Lamp with Surface-Tracking Capability Based on Light Intensity
    (2009)
    Yeh, Lun-Wu
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    Lu, Che-Yen
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    Lin, Yu-Hsuan
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    Liao, Jia-Liang
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    Tseng, Yu-Chee
    The iLamp(1) system is a sensor-enhanced desk lamp with surface-tracking capability based on received light intensity. It consists of two components: lamp and bookmark. The bookmark is a ZigBee-enabled sensor node that can report its sensed light intensity to the lamp with a user-friendly interface and two-way communication capability. The lamp can use its LEDs to locate user's reading surface to which the bookmark is attached, move toward the surface, and further tune its luminous intensity to meet user's preference. We develop the geometrical model for surface tracking. iLamp demonstrates a new centimeter-level location-tracking system using light intensity alone without other extra media or devices.
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    Indoor Localization: Automatically Constructing Today's Radio Map by iRobot and RFIDs
    (2009)
    Yeh, Lun-Wu
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    Hsu, Ming-Shiou
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    Lee, Yueh-Feng
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    Tseng, Yu-Chee
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    資訊工程學系
    For outdoor localization, GPS already provides a satisfactory solution. For indoor localization, however, a globally usable solution is still missing. One promising direction that is proposed recently is the fingerprinting-based solution. It involves a training phase to collect the radio signal strength (RSS) patterns in fields where localization is needed into a database (called radio map). The radio signal could be from WiFi access points, GSM base stations, or other RF-based networks. Then, during the positioning phase, an object which is interested in its own location can collect its current RSS pattern and compare it against the radio map established in the training phase to identify its possible location. We present an interesting system based a robot and numerous cheap RFID tags deployed on the ground to automate the training process and, more importantly, to frequently update radio maps to reflect the current RSS patterns. This not only significantly reduces human labors but also improves positioning accuracy.
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    A WSN-Based Intelligent Light Control System Considering User Activities and Profiles
    (2008-09-01)
    Pan, Meng-Shiuan
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    Yeh, Lun-Wu
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    Chen, Yen-Ann
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    Lin, Yu-Hsuan
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    Tseng, Yu-Chee
    Recently, wireless sensor networks (WSNs) have been widely discussed in many applications. In this paper, we propose a WSN-based intelligent light control system for indoor environments. Wireless sensors are responsible for measuring current illuminations. Two kinds of lighting devices, namely, whole lighting and local lighting devices, are used to provide background and concentrated illuminations, respectively. Users may have various illumination requirements according to their activities and profiles. An illumination requirement is as the combination of background and concentrated illumination demands and users' locations. We consider two requirement models, namely, binary satisfaction and continuous satisfaction models, and propose two decision algorithms to determine the proper illuminations of devices and to achieve the desired optimization goals. Then, a closed-loop device control algorithm is applied to adjust the illumination levels of lighting devices. The prototyping results verify that our ideas are practical and feasible.
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    Autonomous Light Control by Wireless Sensor and Actuator Networks
    (2010-06-01)
    Yeh, Lun-Wu
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    Lu, Che-Yen
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    Kou, Chi-Wai
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    Tseng, Yu-Chee
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    Yi, Chih-Wei
    Recently, wireless sensor and actuator networks (WSANs) have been widely discussed in many applications. In this paper, we propose an autonomous light control system based on the feedback from light sensors carried by users. Our design focuses on meeting users' preferences and energy efficiency. Both whole and local lighting devices are considered. Users' preferences may depend on their activities and profiles and two requirement models are considered: binary satisfaction and continuous satisfaction models. For controlling whole lighting devices, two decision algorithms are proposed. For controlling local lighting devices, a surface-tracking scheme is proposed. Our solutions are autonomous because, as opposed to existing solutions, they can dynamically adapt to environment changes and do not need to track users' current locations. Simulations and prototyping results are presented to verify the effectiveness of our designs.