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Energy optimised IoT assisted multiple fuzzy aggravated energy scheduling approach for smart scheduling systems

  • Hualei Ju
  • , Yixin Chen*
  • , V. Sivakumar
  • , Sivaparthipan C.B
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Presently, Large communication energy is required for the entire project planning system in automation industries. This paper suggests the loss of energy efficiency modeling based on the Multiple Fuzzy Aggravated Energy Scheduling Approach (MFAESA). The Multiple Fuzzy Algorithms Energy Scheduling Approach in assistance with IoT setting builds up and incorporates the fuzzy algorithm in a single objective energy loss problem, based on the preparation period for energy savings and facilities. The algorithm searches the network's idling time and optimizes the task of preparing the energy usage approach to reduce the IoT system's overall energy usage in automation industries. The results show that Multi-Fuzzy Algorithms Energy Scheming outperforms conventional system design which improves accuracy and reduces the execution time.

    Original languageEnglish
    Pages (from-to)951-965
    Number of pages15
    JournalEnterprise Information Systems
    Volume15
    Issue number7
    DOIs
    Publication statusPublished - 2021

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    All Science Journal Classification (ASJC) codes

    • Computer Science Applications
    • Information Systems and Management

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