Author
Listed:
- Manish Bhardwaj
- Shweta Singh
- Shivali Tyagi
- Arun Tripathi
- Yu-Chen Hu
- Rajesh Kumar Tewari
- Anupama Sharma
- Eric Lefevre
Abstract
Pedestrian crossings have also been highlighted as one of the most dangerous locations in the transportation field. Because people and vehicles share the road, a crosswalk improves the road’s efficiency in a densely populated region. However, as the population grows, more accidents and serious injuries occur, and as a result, nationalities are attempting to reduce these incidents through marketing and legal fines. Various architectures and developmental models have been proposed by authors focusing on the safeguarding of pedestrians crossing the intersections and vehicles passing by. Few proposed machine learning and deep learning-based solutions to the pedestrian lanes; others provided an Internet of Things- (IoT-) based solution to the situation. Various challenges are left unresolved, such as evidence recording, image capturing, and recognition in case of an emergency. In the proposed scenario, an IoT-based technology is utilized to assist the vehicles passing by to act over the signals depicted as a red light focusing on a real-time architecture. The proposed system will be mounted along the roadside at the traffic light pole. The system comprises various refined quality components, such as a gesture control module, High Definition camera module, etc. Based on the decision drawn from the gesture module, a specific signal will be displayed with the help of a traffic light to assist the vehicles passing by to safeguard the people crossing the proposed smart pedestrian crossing.
Suggested Citation
Manish Bhardwaj & Shweta Singh & Shivali Tyagi & Arun Tripathi & Yu-Chen Hu & Rajesh Kumar Tewari & Anupama Sharma & Eric Lefevre, 2023.
"A Novel Architecture for the Smart Pedestrian Crossing in Cities Using IoT-Based Approach,"
Mathematical Problems in Engineering, Hindawi, vol. 2023, pages 1-9, September.
Handle:
RePEc:hin:jnlmpe:7334013
DOI: 10.1155/2023/7334013
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:7334013. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.