AI-Powered IoT Solutions for Reducing Carbon Emissions in Smart Cities

Authors

  • Pritha Rai Department of Computer Science & Engineering, PCTE Institute of Engineering and Technology, Ludhiana, Punjab, India.
  • Riya Department of Computer Science & Engineering, PCTE Institute of Engineering and Technology, Ludhiana, Punjab, India

Keywords:

Smart Cities, Carbon Emission Reduction, Sustainable Development, Real-Time Data, Machine Learning, Smart Grids, Traffic Optimization, Renewable Energy

Abstract

As cities grow and energy use increases, reducing carbon emissions while ensuring sustainable development has become a major challenge. This research explores how AI-powered IoT solutions can help lower carbon footprints in urban areas. By using real-time data, machine learning, and automation, these smart systems can improve energy efficiency, traffic flow, waste management, and the use of renewable energy. The study looks at practical applications like smart grids, AI-based traffic control, and predictive maintenance for energy-saving infrastructure. It also highlights how AI can analyze large amounts of environmental data to help policymakers make better decisions. Additionally, the research discusses key challenges such as data security, high costs, and scalability, while suggesting ways to overcome them. The findings show that combining AI and IoT can play a vital role in creating sustainable, low-carbon smart cities, leading to greener and more efficient urban development.

DOI: https://doi.org/10.24321/2393.8307.202505

Published

2026-04-27

Issue

Vol. 12 No. 2 (2025): Journal of Advanced Research in Civil and Environmental Engineering

Section

Research Article