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LANE MORPH: Machine Learning Powered Divider For Traffic Volume Adaptation

Year: 2025

Type: article

Abstract: LaneMorph is a machine learning-powered system designed to optimize urban traffic management using IoT and real-time video processing. By dynamically adjusting road dividers based on traffic density, the system enhances lane utilization, reduces congestion, and prioritizes emergency vehicles. This paper details the architecture, implementation, and potential impact of LaneMorph in smart city infrastructure. Additionally, the system integrates various sensor technologies, predictive algorithms, and automation mechanisms to improve traffic flow efficiency and ensure road safety.

Source: International Journal of Human Computations and Intelligence

DOI: 10.5281/zenodo.14811746

Authors: Lavanya N L, Anvith Krishna N, Arun Kumar V Savanvur, Shrivatsa R S, Udaya Kumar Shetty

Institution: Visvesvaraya Technological University

Language: English

Topic: Traffic control and management

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: diamond

OpenAlex ID: W6930463361

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