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A collaborative sensor network middleware for automated production systems

机译:用于自动化生产系统的协作传感器网络中间件

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摘要

Recent advanced production facilities have utilized networked sensors, which are increasingly designed as e-Work networks with sensor collaboration. Especially, wireless networked microsensors network have been developed and are about to gain widespread use as technology and reliability improve and prices drop. Especially, the redundantly distributed microsensor-based system can significantly and cost-effectively improve the quality of service, processes, and productivity in automated production systems. Besides energy consumption and scalability, a major design challenge, however, is that they must be designed to be adaptable for industrial applications. Most industrial applications require better reliability in communication, robustness to various interferences, fault tolerance, and the geometry of the production facility that collaborating sensors are implemented. Thus, this research proposes a sensor network middleware structure that automated production systems require. The middleware supports optimal or near-optimal multi-sensor deployment scheme and provides solutions for geometry-specific wireless microsensor deployment design. The middleware model is also supported by collaborative e-work network framework. Network design parameters such as the number of sensors, geometry of production facility are being considered to improve reliability of sensory data and to minimize the overall energy consumption under given geometry. Results are also evaluated through specific simulations, applying the Teamwork Integration Evaluator (TIE).
机译:最近的先进生产设备已利用联网的传感器,这些传感器已越来越多地设计为带有传感器协作的e-Work网络。尤其是,随着技术和可靠性的提高以及价格的下降,无线联网的微传感器网络已经得到发展并且将得到广泛使用。特别是,基于冗余分布的基于微传感器的系统可以显着且经济高效地提高自动化生产系统中的服务质量,过程和生产率。除了能耗和可伸缩性之外,主要的设计挑战是必须将其设计为适合工业应用。大多数工业应用需要更好的通信可靠性,对各种干扰的鲁棒性,容错能力以及实现协作传感器的生产设施的几何形状。因此,本研究提出了自动化生产系统所需的传感器网络中间件结构。中间件支持最佳或接近最佳的多传感器部署方案,并为特定于几何的无线微传感器部署设计提供解决方案。协作电子工作网络框架也支持中间件模型。正在考虑使用网络设计参数,例如传感器的数量,生产设施的几何形状,以提高传感数据的可靠性,并在给定的几何形状下将总能耗降至最低。还可以通过使用团队合作集成评估器(TIE)通过特定的模拟来评估结果。

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