Summary: | 博士 === 國防大學理工學院 === 國防科學研究所 === 100 === Equipment is the most capital asset in manufacturing factories. Accompanying with the advancement of technologies, the functions and manufacturing capabilities of equipment have become more complicated and precise, which can be vulnerably spoiled by abnormal power supplies. Thus, a lot of enterprises utilize remote monitoring and control (MC) systems to monitor and maintain the efficacy of the manufacturing equipment. In recent years, wireless sensor network (WSN) technologies are widely applied in various MC applications. In particular, ZigBee is a WSN technology that has the advantages of small size, low power consumption, wireless transmission, and having up to 65535 device nodes in a network. It is very suitable to be applied in many home and industrial MC applications. This dissertation aims to design and develop serveral ZigBee-based intelligent MC architectures and mechanisms. First, a mobile MC architecture is developed by integrating various wireless communication technologies for satisfying various MC demands, such as person identification using RFID, ZigBee indoor positioning, remote MC, and active image push. Next, an intelligent wireless power monitoring architecture with portible deployment capability is created and contains serveral intelligent components, including wireless power monitoring modules, power demand control, power abnormality dectection, and active alarming for abnormalities. Also, a novel data aggregation algorithm is designed to increase the data transmission efficiency of the ZigBee. Finally, a new power monitoring architecture based on cloud computing is proposed, which can leverage the advantages of cloud computing to provide sufficient computing and storage resources on demand for fulfilling the large-scale MC requirements and saving the cost of constructing IT infrastructure. The research results of this dissertation can be a useful reference for developing various MC applications.
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