9,418 research outputs found

    Implementation of RTOS to the WSN node

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    Bezdrátové senzorické sieťe zväčša používajú `event-driven` operačné systémy. Táto práca diskutuje výhody nevýhody použitia RTOS v bezdrátových senzorických sieťach. Najvhodnejší RTOS je vybratý a sú podniknuté všetky kroky aby bolo možne demonštrovať schopnosť mikrokontrolérov Gecko od EnergyMicro prevádzkovať tento RTOS s nízkou spotrebou energie a demonštrovať jednoduchú bezdrátovú komunikáciu s Atmel AT86RF212 rádiami.Wireless sensors networks mostly use event-driven OSes. This works discusses pros and cons of using RTOS in wirless sensors networks. A most appropriate RTOS is chosen and all necessary steps are undergone to demonstrate EnergyMicro Gecko MCU's ability to run the RTOS with low energy consumption and demonstrate wireless simple communication with Atmel AT86RF212 radios.

    An eco-friendly hybrid urban computing network combining community-based wireless LAN access and wireless sensor networking

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    Computer-enhanced smart environments, distributed environmental monitoring, wireless communication, energy conservation and sustainable technologies, ubiquitous access to Internet-located data and services, user mobility and innovation as a tool for service differentiation are all significant contemporary research subjects and societal developments. This position paper presents the design of a hybrid municipal network infrastructure that, to a lesser or greater degree, incorporates aspects from each of these topics by integrating a community-based Wi-Fi access network with Wireless Sensor Network (WSN) functionality. The former component provides free wireless Internet connectivity by harvesting the Internet subscriptions of city inhabitants. To minimize session interruptions for mobile clients, this subsystem incorporates technology that achieves (near-)seamless handover between Wi-Fi access points. The WSN component on the other hand renders it feasible to sense physical properties and to realize the Internet of Things (IoT) paradigm. This in turn scaffolds the development of value-added end-user applications that are consumable through the community-powered access network. The WSN subsystem invests substantially in ecological considerations by means of a green distributed reasoning framework and sensor middleware that collaboratively aim to minimize the network's global energy consumption. Via the discussion of two illustrative applications that are currently being developed as part of a concrete smart city deployment, we offer a taste of the myriad of innovative digital services in an extensive spectrum of application domains that is unlocked by the proposed platform

    Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

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    Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

    A Survey on IT-Techniques for a Dynamic Emergency Management in Large Infrastructures

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    This deliverable is a survey on the IT techniques that are relevant to the three use cases of the project EMILI. It describes the state-of-the-art in four complementary IT areas: Data cleansing, supervisory control and data acquisition, wireless sensor networks and complex event processing. Even though the deliverable’s authors have tried to avoid a too technical language and have tried to explain every concept referred to, the deliverable might seem rather technical to readers so far little familiar with the techniques it describes
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