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  • 1.
    Yan, J.
    et al.
    Institute of Lightwave Technology, Beijing Jiaotong University, Beijing 100044, China.
    Pei, L.
    Institute of Lightwave Technology, Beijing Jiaotong University, Beijing 100044, China.
    Chen, Z.
    Institute of Lightwave Technology, Beijing Jiaotong University, Beijing 100044, China.
    Wang, Mengjiao
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Local adaptive sampling for wireless sensor network powered by energy harvesting2012In: Optik (Stuttgart), ISSN 0030-4026, Vol. 123, no 23, 2195-2197 p.Article in journal (Refereed)
    Abstract [en]

    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. 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. © 2011 Elsevier GmbH. All rights reserved.

  • 2.
    Yan, Junfang
    et al.
    Beijing Jiaotong University, Beijing, China.
    Pei, Li
    Beijing Jiaotong University, Beijing, China.
    Wang, Mengjiao
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Liu, Chao
    Beijing Jiaotong University, Beijing, China.
    Gao, Song
    Beijing Jiaotong University, Beijing, China.
    Local adaptive sampling for an energy harvesting CO2 sensor2011In: IET Conference Publications, IEEE, 2011Conference paper (Refereed)
    Abstract [en]

    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 C02 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.

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