Application of metaverse technologies and artificial intelligence in smart cities
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.2.60Keywords:
Metaverse, Artificial intelligence, Smart cities, Environment pollution.Dimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The metaverse has been the subject of a global trend in recent years. A network of connected, immersive digital areas where people can engage with computer-generated settings is called the metaverse. The realm of the metaverse possesses the potential to fundamentally change and alter smart cities—urban areas that aim to enhance citizen experiences by accelerating economic growth, modernizing government functions, enhancing accessibility, and promoting sustainability. In this article, we explore how utilizing the metaverse to power smart cities might spur substantial advancements and breakthroughs. The primary technologies that facilitate the metaverse are examined, along with the advantages of using this technology and its potential for smart city bids. We presented multiple instances and looked at the main opportunities that the metaverse provides for smart cities in order to show how the technology of the metaverse has helped and enriched a range of enterprises. Subsequently, five models of neural networks were chosen from the literature to be utilized in the air quality prediction process and evaluated based on accuracy. Therefore, the innovative model combination of ANN and DLR as an aid for decision-making and problem-solving can favorably regulate air pollution in order to handle environmental challenges.Abstract
How to Cite
Downloads
Similar Articles
- Rianka Sarkar, P. Sreeramulu, Oceanic Epistemologies and Trans-corporeality: Reimagining Amitav Ghosh through Anthropocene Narratives , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- B. R. JAIPAL, POPULATION STRUCTURE OF NILGAI (BOSELAPHUS TRAGOCAMELUS) IN THE SEMI ARID REGION OF THE THAR DESERT , The Scientific Temper: Vol. 10 No. 1&2 (2019): The Scientific Temper
- Shobhit Shukla, Suman Mishra, Gaurav Goel, River flow modeling for flood prediction using machine learning techniques in Godavari river, India , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Sruthy M.S, R. Suganya, An efficient key establishment for pervasive healthcare monitoring , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- R. Sakthiraman, L. Arockiam, RFSVMDD: Ensemble of multi-dimension random forest and custom-made support vector machine for detecting RPL DDoS attacks in an IoT-based WSN environment , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
- Raja Pathak, Shweta Kumari, An investigation on the impact of vedic mathematics on higher secondary school student’s ability to expand mathematical units , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- Jumman Bakhasha, Kamlesh K. Yadav, Vaishnavi Saxena, Neeti Arya, Abha Trivedi, Environmentally relevant concentration of copper elated hematological impairment, branchiotoxicity, myotoxicity, nephrotoxicity and antioxidants imbalance in fish Channa punctatus , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Archana Verma, Role of artificial intelligence in evaluating autism spectrum disorder , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper

