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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Recently, wireless sensor networks have been widely discussed in many applications. In this paper, we propose a novel 3D emergency service that aims to guide people to safe places when emergencies happen. At normal time, the network is responsible for monitoring the environment. When emergency events are detected, the network can adaptively modify its topology to ensure transportation reliability, quickly identify hazardous regions that should be avoided, and find safe navigation paths that can lead people to exits. In particular, the structures of 3D buildings are taken into account in our design. Simulation results shows that our protocols can adapt emergencies quickly at low message cost and can find safer paths to exits than existing results.

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Convergecast is a fundamental operation in wireless sensor networks. Existing convergecast solutions have focused on reducing latency and energy consumption. However, a good design should be compliant to standards, in addition to considering these factors. Based on this observation, this paper defines a minimum delay beacon scheduling problem for quick convergecast in ZigBee tree-based wireless sensor networks and proves that this problem is NP-complete. Our formulation is compliant with the lowpower design of IEEE 802.15.4. We then propose optimal solutions for special cases and heuristic algorithms for general cases. Simulation results show that the proposed algorithms can indeed achieve quick convergecast.

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It has long been recognized that ocean gravity waves can generate microseisms through their interactions and coupling with the solid earth. Their generation mechanisms, wave types, and propagation have been studied and debated intensively. In this study, we focus on the characteristics of microseisms in South China Sea (SCS) and compare them with globally observed microseisms. We use data from six ocean bottom seismometers, 10 publicly available broadband land seismometers near SCS, and a reanalyzed global wave height model from 1 May 2012 to 20 August 2012 (UTC), the time span of ocean bottom seismometers' data. We apply three techniques including power spectral density, correlation, and frequency dependent polarization analysis. Our results show that (1) microseisms observed in SCS are dominated by sources from adjacent oceans, instead of the common global sources from the Pacific, Atlantic, or Indian Ocean; (2) the split of double-frequency microseisms (DFMs) is observed in SCS, especially on land stations: the sources are located near the central sea basin for long-period DFMs (0.1-0.25 Hz) and are local near stations for short-period DFMs (0.25-0.5 Hz); (3) typhoons both strengthen microseisms and affect the source locations of microseisms with the biggest influence on the short-period DFMs; and (4) microseisms in or near SCS are a mixture of Love and Rayleigh waves and the relative dominance of Love and Rayleigh waves changes with locations.As early as the 1900s when microseisms were still treated as one group, there were mainly two candidates on the source locations: one was coastal region (e.g., Gutenberg, 1931;Haubrich, 1963) and the other was open ocean (e.g., Banerji, 1930; Haq, 1954). Although Stehly et al. (2006) back-projected the source of SFMs to the XIAO ET AL. 3923

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