A Study on an Enhanced Traffic Control System for Road Vehicles Using Raspberry Pi | Chapter 1 | Advances and Challenges in Science and Technology Vol. 4

 The experience's population is increasing by every day, so as the state grows, so are the number of buses on the road. Managing traffic is becoming more difficult for those administrative of traffic. The traffic is high at the intersections, that is causing extra questions for emergency jeeps such as ambulances, fire appliances, and police jeeps. The traffic on the roads results in time wasted and a rise in dirtiness levels. Previously, magnetic loop detectors were used to control traffic, but now we exploit RFID tags for emergency tools and RFID readers at intersections. The traffic signal system is controlled using Raspberry Pi, RFID tags for danger vehicles, and RFID readers at traffic intersections, in addition to a dynamic color change invention.

Author(s) Details:

Bura Vijay Kumar,
Center for Embedded Systems & Internet of Things, Department of Computer Science and Engineering, S R University, Warangal, Telangana, India.

A. Harshavardhan,
Department of Computer Science and Engineering, S R University, Warangal, Telangana, India.

P. Kumaraswamy,
Department of Computer Science and Engineering, S R University, Warangal, Telangana, India.

K. Sangameshwar,
Kakatiya Institute of Technology and Science, Warangal, Telangana, India.

D. Kothandaraman,
Center for AI & Deep Learning, Department of Computer Science and Engineering, S R Engineering College, Warangal, Telangana, India.

Gotte Ranjith Kumar,
Jyothishmathi Institute of Technology and Science, Karimnagar, Telangana, India.

Please see the link here: https://stm.bookpi.org/ACST-V4/article/view/12093

Safety Systems in Car Using Raspberry-Pi | Chapter 9 | Advanced Aspects of Engineering Research Vol. 8

 Automobile accidents result in not just human fatality but also financial costs to both individuals and society. This special issue examines the history and backdrop of the automobile system while also highlighting modern advances. This study seeks to provide an overview of the current and future implementation of safety and security systems in automobiles. Drowsiness detection and the Anti pinch window effect are two crucial enabling technologies for active safety systems. Seat belt detection and alcohol detection are two more concepts that have been presented for implementation. The tiredness of drivers is tracked using an image processing methodology that is run through MATLAB. However, the fundamental limitation of this methodology is the processing speed on hardware. The aim described in this research is to use the Open CV library for real-time facial image analysis to detect driver tiredness and thereby avoid traffic accidents. Power window injuries can be avoided with the deployment of an anti-pinch window mechanism. The seat belt alert system emits an audible signal to remind people to buckle up for safety. Finally, if alcohol detection finds a drunk driver, a message with the vehicle's details and location is sent to a local police station. The suggested system accomplishes all of the aforementioned functions with the help of a Raspberry-Pi, camera, and a few sensors in its hard ware, as well as coding computations in Python, which provides the benefit of continuous monitoring at a low cost, hence reducing unintentional accidents to a considerable amount. The suggested system is a demonstration version of an automobile safety system that makes use of open CV software and associated hardware. Because this detection is based on a high-resolution camera, it will be more accurate.

Author (s) Details

S. Sharmila Devi
Department of Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore-22, Tamil Nadu, India.

View Book :- https://stm.bookpi.org/AAER-V8/article/view/1104