An Implementation of Efficient Smart Street Lights with Crime and Accident Monitoring: A Review

Main Article Content

Chua Tze Yong, Chan Vei Hao, Basheer Ruskhan, Selina Kam Yee Lim, Tan Gian Boon , Then Sze Wei, Sumathi Balakrishnan. Imdad Ali Shah

Abstract

 


Smart street lights with crime and accident monitoring are the technology that adds sensors and cameras to regular street lights to make public roads safer and more secure. These smart streetlights have motion sensors, cameras, and other detection tools that can pick up on possible crimes or accidents and let the police know. They can also collect data on traffic patterns, weather conditions, and other factors that can affect public safety. The data collected from these smart streetlights can be analyzed using artificial intelligence (AI) and machine learning algorithms to identify patterns and trends that can help authorities make informed decisions about how to improve public safety. For example, if the data shows that a particular intersection is prone to accidents, management can improve road infrastructure or increase police presence there. Smart streetlights with crime and accident monitoring can help improve public safety and reduce crime rates by providing real-time monitoring and analysis of public spaces. They can also work with other smart city technologies to make cities more efficient and environmentally friendly. The primary objective of this research article is to find the solution to the problem above in the form of smart streetlights (SSL), a type of smart device capable of communicating with each other wirelessly, relaying important sensor data or video data to improve the usability of the city. Further, this article consists of numerous literature reviews, methodology, and analysis of findings, such as how the authors abstracted the findings and results from the literature review. The authors have also included an implementation of the Tinkercad workflow to showcase the complete circuit board.

 

Article Details

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Articles
Author Biography

Chua Tze Yong, Chan Vei Hao, Basheer Ruskhan, Selina Kam Yee Lim, Tan Gian Boon , Then Sze Wei, Sumathi Balakrishnan. Imdad Ali Shah