STO: A Dynamic AIoT-Based Approach for Energy-Efficient Urban Traffic Management

Document Type

Conference Proceeding

Source of Publication

IEEE International Conference on Communications

Publication Date

9-26-2025

Abstract

Urban congestion and environmental pollution are pressing issues in urban sustainability. This study introduces the Streamlined Traffic Optimizer (STO), an AIoT-based system designed to improve urban traffic flow and reduce energy consumption. The STO algorithm dynamically adapts traffic signals using real-time data from the Uber Movement dataset. Initial results from simulations show a significant reduction in average travel time from 35 minutes to 28 minutes and an increase in average speed from 30 km/h to 36 km/h. Additionally, congestion levels dropped from 40% to 25%, while fuel consumption decreased by 18%, from 10,000 liters to 8,200 liters. These improvements are accompanied by a reduction in CO2 emissions from 1,200 to 950 tons per year. The STO system offers a scalable and flexible solution for cities aiming to reduce their environmental impact while optimizing traffic efficiency.

ISBN

[9798331505219]

ISSN

1550-3607

Publisher

IEEE

First Page

4221

Last Page

4226

Disciplines

Computer Sciences

Keywords

Intelligence of Things, Scalability, Traffic Management, Traffic Predictions

Scopus ID

105018458185

Indexed in Scopus

yes

Open Access

no

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