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Local adaptive sampling for an energy harvesting CO2 sensor

机译:用于能量收集CO2传感器的本地自适应采样

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For a sensor network, energy limitation is always a key factor to affect the continuous work of a sensor node. A good idea is harvesting energy from the environment to support the node to work continuously. However, energy from environment is varied with time, weather and season. So in order to use the varied environment energy, it is necessary to find a way to achieve real-time monitoring and adaptive working. In this paper, an algorithm called “Adaptive Sampling” was proposed to adapt the sample mode to the present energy condition. And solar energy is proposed as the energy source to power the system. Simulation proves that the algorithm can make the CO2 sensor flexibly achieve adaptive sampling under different energy condition with the least MSE 2.7767. This algorithm can be widely used in wireless sensor network power by energy harvesting for local adaptive sampling.
机译:对于传感器网络,能量限制始终是影响传感器节点连续工作的关键因素。一个好主意是从环境中收集能量以支持节点连续工作。但是,环境能量随时间,天气和季节而变化。因此,为了利用变化的环境能量,有必要找到一种实现实时监视和自适应工作的方法。在本文中,提出了一种称为“自适应采样”的算法,以使采样模式适应当前的能量条件。提出了将太阳能作为为系统供电的能源。仿真结果表明,该算法可以使MS2最小,能灵活地在不同能量条件下实现CO2传感器的自适应采样。该算法可通过能量收集进行局部自适应采样,从而广泛用于无线传感器网络电源。

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