AI-Enabled IoT for smart cities and infrastructure
Department of Computer Science Engineering, Government Polytechnic Kudligi, Karnataka, India.
Research Article
World Journal of Advanced Research and Reviews, 2021, 09(02), 205-213
Publication history:
Received on 02 February 2021; revised on 10 February 2021; accepted on 27 February 2021
Abstract:
The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) is revolutionizing urban development by enabling smarter, more efficient, and sustainable cities. AI-powered IoT systems integrate real-time data processing, predictive analytics, and automation to enhance various aspects of urban infrastructure, leading to improved resource utilization, reduced operational costs, and enhanced citizen services. This paper explores the transformative role of AI-enabled IoT in key smart city applications, including intelligent transportation, energy management, waste management, and public safety. In intelligent transportation, AI-driven IoT solutions optimize traffic flow, reduce congestion, and improve public transit efficiency through predictive modeling, autonomous vehicle integration, and adaptive traffic management systems. Energy management benefits from AI-enabled IoT networks that analyze consumption patterns, enhance grid stability, and facilitate the seamless integration of renewable energy sources, contributing to sustainable urban power distribution. In waste management, AI-powered IoT applications enable smart waste collection, optimize route planning, and enhance recycling processes through automated monitoring and real-time analytics. Furthermore, AI-driven public safety applications, including intelligent surveillance, emergency response systems, and crime prediction models, enhance urban security and disaster preparedness. This study presents various AI-driven IoT frameworks, highlighting their benefits, technological capabilities, and implementation challenges. Issues such as data privacy, cybersecurity, infrastructure scalability, and interoperability are analyzed in detail to assess the feasibility and long-term sustainability of these smart city solutions. Through an in-depth review of existing case studies and emerging trends, this research provides insights into how AI-enabled IoT can shape the future of urban development. Tables, figures, and bar charts illustrate key technological advancements, deployment strategies, and the overall impact of AI-driven IoT systems on modern urban infrastructure. By addressing existing challenges and leveraging the full potential of AI and IoT integration, cities can enhance operational efficiency, improve quality of life, and foster sustainable development in an increasingly digital world.
Keywords:
AI; IoT; Smart Cities; Infrastructure; Machine Learning; Automation; Data Analytics
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Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0