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    Poster Abstract: Decentralized energy and power estimation in solar-powered wireless sensor networks

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    Type
    Conference Paper
    Authors
    Dehwah, Ahmad H.
    Taieb, Souhaib Ben
    Shamma, Jeff S. cc
    Claudel, Christian G.
    KAUST Department
    Applied Mathematics and Computational Science Program
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Electrical and Computer Engineering Program
    RISC Laboratory
    Date
    2015
    Permanent link to this record
    http://hdl.handle.net/10754/670640
    
    Metadata
    Show full item record
    Abstract
    Solar powered wireless sensor networks are very adapted to smart city applications, since they can operate for extended durations with minimal installation costs. Nonetheless, they require energy management schemes to operate reliably, unlike their grid-powered counterparts. Such schemes require the forecasting of future solar power inputs for each wireless sensor node, over a time horizon. They also require the determination of battery energy parameters in real time. To address both requirements, we propose a collaborative solar power forecasting framework combined to a real time battery capacity estimation model, which can be used to optimize the node schedules over the corresponding horizon.
    Citation
    Dehwah, A. H., Taieb, S. B., Shamma, J. S., & Claudel, C. G. (2015). Decentralized Energy and Power Estimation in Solar-Powered Wireless Sensor Networks. 2015 International Conference on Distributed Computing in Sensor Systems. doi:10.1109/dcoss.2015.18
    Publisher
    IEEE
    Conference/Event name
    11th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2015
    ISBN
    9781479988563
    DOI
    10.1109/DCOSS.2015.18
    Additional Links
    http://ieeexplore.ieee.org/document/7165038/
    ae974a485f413a2113503eed53cd6c53
    10.1109/DCOSS.2015.18
    Scopus Count
    Collections
    Conference Papers; Applied Mathematics and Computational Science Program; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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