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Multiple-Embedded-System Optimization Layout for Electromagnetic Wave Power Density in Complex Environments

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  • Yang-Hsin Fan

    (Department of Computer Science and Information Engineering, National Taitung University, Taitung 95092, Taiwan)

Abstract

Many embedded systems are implemented for healthcare, and smart homes and spaces. These devices are generally designed for elderly care, for monitoring, surveillance, and collection information. As embedded systems are ubiquitous and pervasive in a smart home, office, or space, different layout affects not only reduce the implementation cost but also the power density of electromagnetic waves. This study aimed to develop a multiple-embedded-system optimization layout to consume less electromagnetic wave power density and gain better communication strength. For smart offices, we analyzed the layout topology of n -shaped and n -shaped with door layout categories. On the basis of the location of each embedded system in a communication center via an n -shaped layout, we investigated the electromagnetic wave effect to the local, direct, and semidirect effects. Indirect and subindirect effects were also studied in the n -shaped layout with a door. In addition, we derived a set of formulas from the scope for the diverse effects to help users to quickly identify the scope of each effect. To verify the multiple-embedded-system optimization layout, 16 cooperating embedded systems with four test cases in a smart office were used to evaluate the diverse effects of electromagnetic wave power density and communication strength. Experiment results showed that the optimization layout consumed 3950 × 10 −6 W/m 2 electromagnetic wave power density.

Suggested Citation

  • Yang-Hsin Fan, 2020. "Multiple-Embedded-System Optimization Layout for Electromagnetic Wave Power Density in Complex Environments," Energies, MDPI, vol. 13(18), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4758-:d:412577
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    References listed on IDEAS

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    1. Yang-Hsin Fan, 2018. "Energy-Efficient Clusters for Object Tracking Networks," Energies, MDPI, vol. 11(8), pages 1-12, August.
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