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Smart energy optimization for massive IoT using artificial intelligence

  • University of Houston
  • Florida International University
  • Florida International University
  • California State University, Fullerton
  • University of Houston-Victoria

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

The concept of a connected world using Internet of Things (IoT) has already taken pace during this decade. The efficient hardware and high throughput networks have made it possible to connect billions of devices, collecting and transmitting useable information. The benefit of IoT devices is that they enable automation however, a significant amount of energy is required for billions of connected devices communicating with each other. This requirement of energy, unless managed, can be one of the barriers in the complete implementation of IoT systems. This paper presents the energy management system for IoT devices. Both hardware and software aspects are considered. Energy transparency has been achieved by modelling energy consumed during sensing, processing, and communication. A multi-agent system has been introduced to model the IoT devices and their energy consumptions. Genetic algorithm is used to optimize the parameters of the multi-agent system. Finally, simulation tools such as MATLAB Simulink and OpenModelica are used to test the system. The optimization results have revealed substantial energy consumption with the implementation of decentralized intelligence of the multi-agent system.
Original languageEnglish
Article number100354
JournalInternet of Things (Netherlands)
Volume13
Issue numberIssue
DOIs
StatePublished - Mar 1 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

Keywords

  • 5G
  • Artificial intelligence
  • Energy conservation
  • Internet of things
  • Massive IoT
  • MATLAB
  • Multi-agent systems

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