Abstract-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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Volatile resistive switching random access memory (RRAM) devices are drawing attention in both storage and computing applications due to their high ON-/OFF-ratio, fast switching speed, low leakage, and scalability. However, these devices are relatively new and the physical switching mechanisms are still under investigation. A thorough understanding and modeling of the physical dynamics underlying filament formation and self-dissolution are of utmost importance in view of future integration of volatile devices in neuromorphic systems and in memory arrays. To assess the physical mechanisms and develop appropriate models, though, the electrical properties of the device have to be characterized. In this article, we present an extensive study of Ag/SiO x -based volatile RRAM devices. Important parameters, such as switching time, switching voltage, and retention time are investigated as a function of the stimulation conditions. A physical explanation is provided and the applicability of the device in neuromorphic systems is discussed.

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