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Location-specific optimization of energy harvesting environmental monitoring systems

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86093264" target="_blank" >RIV/61989100:27240/14:86093264 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/INTELES.2014.7008979" target="_blank" >http://dx.doi.org/10.1109/INTELES.2014.7008979</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/INTELES.2014.7008979" target="_blank" >10.1109/INTELES.2014.7008979</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Location-specific optimization of energy harvesting environmental monitoring systems

  • Original language description

    Environmental sensing is necessary for air quality monitoring, assessment of ecosystem health, or climate change tracking. Environmental monitoring systems can take a form of standalone monitoring stations or networks of individual sensor nodes with wireless connectivity. The latter approach allows high resolution mapping of spatiotemporal characteristics of the environment. To allow their autonomous operation and to minimize their maintenance costs, such systems are often powered using energy harvested from the environment itself. Due to the scarcity and intermittency of the environmental energy, operation of energy harvesting monitoring systems is not a trivial task. Their sensing, transmitting, and housekeeping activities must be carefully managed to extend their lifetime while providing desired quality of service. As the environmental conditions change with the region of deployment, the strategies for energy management must change accordingly to match the energy availability. In this work, we examine how geographic location affects the operations and quality of data collected by a solar-powered monitoring system. In particular, we use node/network simulation tools to follow the performance of energy-harvesting environmental monitoring sensor nodes at different latitudes, from equator to the pole. Static parameters of the simulated sensor nodes are determined for each latitude using an intelligent optimization method. The results show a clear dependence of the monitoring system performance on its deployment location. This encourages location-specific optimization of sensor node properties and parameters

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - IES 2014: 2014 IEEE Symposium on Intelligent Embedded Systems, Proceedings

  • ISBN

    978-1-4799-4486-6

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    8-13

  • Publisher name

    IEEE

  • Place of publication

    New York

  • Event location

    Orlando

  • Event date

    Dec 9, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000363908600002