Intelligent Computational Model for Energy Efficiency and AI Automation of Network Devices in 5G Communication Environment

Ashish Bagwari, Jaganathan Logeshwaran, M. Raja, P. Devisivasankari, Jyotshana Bagwari, Vikas Rathi, Asma Mohammed Elbashir Saad

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Currently, the 4G network service has caused massive digital growth in high use. Video calling has become the go-to Internet application for many people, downloading even huge files in minutes. Everyone is looking for and buying only 4G Subscriber Identity Module (SIM)-capable mobiles. In this case, the expectation of 5G has increased in line with 2G, 3G, and 4G, where the G stands for generation, and it does not indicate Internet or Internet speed. 5G includes next-generation features that are more advanced than those available in 4G network services. The main objective of 5G is uninterrupted telecommunication service in hybrid energy storage system. This paper proposes an intelligent networking model to obtain the maximum energy efficiency and Artificial Intelligence (AI) automation of 5G networks. There is currently an issue where the signal cuts out when crossing an area with one tower and traveling to an area with another tower. The problem of 'call drop', where the call is disconnected while talking, is not present in 5G. The proposed Intelligent Computational Model (ICM) model obtained 96.31% network speed management, 90.63% battery capacity management, 92.27% network device management, 93.57% energy efficiency, and 88.41% AI automation.

Original languageEnglish
Pages (from-to)1728-1751
Number of pages24
JournalTsinghua Science and Technology
Volume29
Issue number6
DOIs
StatePublished - 1 Dec 2024

Keywords

  • 4G
  • 5G
  • Artificial Intelligence (AI) automation
  • Subscriber Identity Module (SIM)
  • digital growth
  • downloading
  • energy efficiency
  • generation
  • hybrid energy
  • network
  • storage system

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