Conceptual Design of Smart Network Adaptive Traffic Light in Creating Low-Carbon City

• Published in: INTERNATIONAL JOURNAL OF INTEGRATED ENGINEERING
• Main Authors: Misnan, Mohamad Farid; Thamrin, Norashikin M.; Amin, Megat Syahirul Megat; Abu Bakar, Zahari
• Format: Article
• Language: English
• Published: UNIV TUN HUSSEIN ONN MALAYSIA 2023
• Subjects: Engineering
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001133059700003

The research is led to the development of a smart sensory network adaptive traffic light to optimise traffic flow and reduce congestion on Jalan Persisiran Seri Alam in Pasir Gudang. With variable time management, this system can reduce the time spent at traffic junctions and carbon emitted by vehicles, thus supporting the SDG 11 for low carbon smart city. By integrating the dynamic duration of each traffic signal on each dense pathway, this system can help to reduce traffic congestion, fuel consumption, and CO2 emissions. It can also ensure that traffic is managed in a more efficient manner, thus improving the quality of life for the people of Pasir Gudang. The success of this system will be a major step towards achieving the goal of a low carbon smart city, as it will help to reduce air pollution, noise pollution, and improve road safety. Additionally, it can help to improve the efficiency of traffic flow, leading to better traffic management and reduced congestion.