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IJSTR >> Volume 10 - Issue 6, June 2021 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Iot Enabled Intelligent Traffic Congestion Handling System Empowered By Machine Learning

[Full Text]

 

AUTHOR(S)

Farhad Hassan, Amir Ijaz, Mubashir Ali, Zeshan Afzal, Farrukh Arslan

 

KEYWORDS

Internet of Things, Machine Learning, Traffic Management, Congestion Control, Smart Cities, Mathematical Modeling.

 

ABSTRACT

Internet of things is evolving technology which driving the world towards automation and smart systems. It is major factor of industry 4.0, smart cities and smart societies. Currently, the traffic is increasing exponentially in big cities; control and management of traffic in smart cities is well-known issue. Efficient congestion control and traffic management save many valuable resources. Various sensors are integrated in automated and smart systems to sense, collect and transfer data. Machine learning is another emerging technology that improves the intelligence and capabilities of smart systems. In this paper, we proposed an IoT-ITCHS-ML model to sense, analyze and control the traffic congestion in smart societies. The proposed system sense and notify the congested areas. The proposed systems performed significantly well in comparison with previous approaches and obtain 99.2% accuracy with only 1.2% missrate in training phase; 98.5% accuracy in validation phase. This research prosper the smart systems, IoT innovations and impact of machine learning in smart societies.

 

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