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 (Proceeding of the International Conferences on Engineering Sciences, 2025)
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.