Enhancing Urban Sustainability through AI-Driven Energy Efficiency Strategies in Cloud-Enabled Smart Cities

https://doi.org/10.55529/jeet.45.1.13

Authors

  • Anil Kumar Jakkani Research Consultant, the Brilliant Research Foundation Pvt. Ltd., Hyderabad, India.

Keywords:

Energy Efficiency, Smart Cities, Urban, Cloud, AI, Sustainability.

Abstract

Energy efficiency in the modern urban environment is fostered by high technologies like artificial intelligence (AI), cloud computing and others. Thus, this research aims at examining the adoption of AI solutions in the climate-smart cities using cloud technology to boost the achievement of the sustainable development goals. With data collected from the IoT sensors that are integrated within different structures of the city, the AI will be able to actively regulate the energy usage as needed in real time. Such algorithms not only predict energy requirements but also adapt the entire city’s functioning to decrease losses and harm the environment less. Cloud computing is instrumental by integrating large amounts of storage and processing that are required in tackling data accrued by the IoT devices. By way of cases and experiments, this research assesses how AI-based solutions can address problems of emerging city carbon footprint and sustainability under various urban conditions. The purpose of this research work is to highlight the importance of artificial intelligence and cloud computing to enhance the urban environment’s entity. They present these technologies showing their potential in shedding light on the rational use of energy in various facets of city functioning, and in this manner they make a positive impact on the drive for attaining sustainable development goals.

Published

2024-08-05

How to Cite

Anil Kumar Jakkani. (2024). Enhancing Urban Sustainability through AI-Driven Energy Efficiency Strategies in Cloud-Enabled Smart Cities. Journal of Energy Engineering and Thermodynamics, 4(5), 1–13. https://doi.org/10.55529/jeet.45.1.13

Similar Articles

<< < 1 2 3 4 5 > >> 

You may also start an advanced similarity search for this article.