Smart Traffic Management System for Reducing Urban Congestion in Major Indonesian Cities Using IOT and AI Technologies

Michael Thobie Rahadian Kartono; Nuvia Kurnia Sari; Andi Trio Suroso

doi:10.61132/iconfes.v2i1.14

Authors

Michael Thobie Rahadian Kartono Universitas Udayana (Unud)
Nuvia Kurnia Sari Universitas Udayana (Unud)
Andi Trio Suroso Universitas Udayana (Unud)

DOI:

https://doi.org/10.61132/iconfes.v2i1.14

Keywords:

Traffic management, IoT, AI, urban congestion, smart city, Indonesia

Abstract

Urban traffic congestion is a growing problem in Indonesian cities, affecting economic productivity and quality of life. This research explores the development of a smart traffic management system utilizing Internet of Things (IoT) sensors and artificial intelligence (AI) algorithms to analyze traffic patterns and optimize flow. The proposed system collects real-time data and uses predictive analytics to adjust traffic signals dynamically. Field tests in Jakarta demonstrate a 15% improvement in traffic flow and reduced travel times during peak hours. The findings suggest significant potential for scalable smart city solutions in urban traffic management across Indonesia.

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