Integrating IoT and AI for Smart Urban Planning

Authors

  • Alex Wright
  • Adrian Martinez
  • Quinn Evans

Keywords:

iot, artificial intelligence, urban planning, smart cities, public services

Abstract

This article examines the integration of Internet of Things (IoT) and artificial intelligence (AI) technologies to innovate smart urban planning. By utilizing data collected from IoT sensors, the study explores AI-driven analytics to improve urban infrastructure, reduce traffic congestion, and enhance public services. The research outlines a framework for implementing AI-enhanced IoT systems in urban environments, highlighting case studies in smart city initiatives. The findings demonstrate the transformative potential of IoT and AI in creating more efficient, sustainable, and livable urban spaces. This work contributes to the evolving field of intelligent urban development.

Author Biographies

Alex Wright

PhD in Urban Planning
Sorbonne Université
4 Place Jussieu, 75005 Paris, France

Adrian Martinez

PhD in Computer Science
Kharkiv National University of Radio Electronics
Nauky Ave, 14, Kharkiv, Kharkiv Oblast, 61166, Ukraine

Quinn Evans

PhD in Information Technology
University of São Paulo
Av. Prof. Luciano Gualberto, 380 - Butantã, São Paulo - SP, 05508-010, Brazil

References

Satyanarayana, D., Rathinam, G., Al Kalbani, A. S., Idries, N. K. S., & Al Azzani, A. (2024, March). A Robot Navigation Method Using Restricted Minimum Spanning Tree. In 2024 10th International Conference on Electrical Engineering, Control and Robotics (EECR) (pp. 155-159). IEEE.

Published

2024-08-12

Issue

Section

Articles