Energy Aware Green 6G IoT Architecture for Sustainable Smart City Development Supporting SDG 7
Year: 2025
Type: article
Abstract: Cities are getting more crowded, which means that people need to use energy more efficiently. As cities become more complicated, using the power of sixth generation (6G) wireless networks along with the Internet of Things (IoT) is turning out to be a good way to make energy ecosystems that last. This paper shows a 6G-IoT architecture that takes energy into account and is meant to be used in smart cities. The goal is to use as much energy as possible and throw away as little as possible. The suggested framework combines the very low latency of 6G with smart IoT nodes that can keep an eye on energy use, allocate and control power resources in real time, and do predictive control. It also uses edge computing and machine learning to better handle local data, which helps cut down on both latency and carbon emissions. The energy-aware protocol automatically adjusts the supply and demand of energy between the connected urban areas, such as transportation, utilities, and residential networks, in a way that saves energy. The simulation results show that this method not only makes communication more reliable and energy use more efficient, but it also makes IoT frameworks more sustainable overall. The model directly supports Sustainable Development Goal 7 (Affordable and Clean Energy) by encouraging a more environmentally friendly way to use energy. The main point of this research is that the combination of 6G and IoT can change the way cities get their energy, making networks that are more flexible, resilient, and sustainable, and that can meet the needs of future cities.
Source: Elaris Computing Nexus
DOI: 10.65148/ecn/2025022
Authors: Kanev Boris Lisitsa, Babithalincy R
Institutions: University of Liverpool, Sri Eshwar College of Engineering
Topic: IoT and Edge/Fog Computing
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4417075125
