Enabling Sustainable Energy for Smart Environment Using 5G Wireless Communication and Internet of Things

D. Hemanand*, D. S. Jayalakshmi, Uttam Ghosh, A. Balasundaram, Pandi Vijayakumar, Pradip Kumar Sharma

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


Energy production, management, distribution, and effective consumption have become an uphill challenge, especially digital disruption and tech-nological advancements. Most of the technology enablers and devices demand continuous energy supply for uninterrupted operation. Effective ener-gy management is essential to ensure that optimal energy is distributed across the intended devices and not wasted. Hence, the need for sustainable energy in power distribution and management is magnified. This work focuses on developing a robust sustainable energy distribution approach to distribute generated energy across needy devic-es effectively. This approach leverages technol-ogy enablers' services like the Internet of Things (IoT) to sense the energy demand of individual devices and 5G wireless communication for faster communication of IoT sensors with devices and to ensure sustained energy availability for them. The existing Glow worm Swarm Optimization approach is applied across IoT sensors to detect the devices in need of energy and distribute optimal energy on a need basis to accomplish smart, sustainable energy management. The approach's performance is determined in terms of optimal energy distribution based on energy demand and supply and is reported.

Original languageEnglish
Pages (from-to)56-61
Number of pages6
JournalIEEE Wireless Communications
Issue number6
Publication statusPublished - 1 Dec 2021


  • 5G wireless communication
  • energy production
  • power distribution
  • technol-ogy enablers
  • energy demand supply
  • IoT sensors
  • smart energy management
  • optimal energy distribution
  • smart environment
  • distribute generated energy
  • Internet of Things
  • glow worm swarm optimization approach


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