Adil Khan 11 months ago
AdiKhanOfficial #FYP Ideas

Helmet Detection

As day by day, most bike riders cause serious injuries. To save these type of serious issue Government impose some rules on the public like as helmet wearing law(PMVO 1969, 89- A) according to this law a bike ride should have to wear a helmet before riding a bike. Nowadays this law is imposed on the

Project Title

Helmet Detection

Project Area of Specialization

Artificial Intelligence

Project Summary

As day by day, most bike riders cause serious injuries. To save these type of serious issue Government impose some rules on the public like as helmet wearing law(PMVO 1969, 89- A) according to this law a bike ride should have to wear a helmet before riding a bike. Nowadays this law is imposed on the public by the traffic police manually. A traffic cop sees a person not wearing a helmet and fine (1,000) him according to the rule. But there is an issue that some persons may not be detected by him and some persons may run away. To resolve this issue we will work on automated helmet detection by road cameras and impose a fine on a person violating the rule automatically by detecting his face.

Project Objectives

As day by day, most bike riders cause serious injuries. To save these type of serious issue Government impose some rules on the public like as helmet wearing law(PMVO 1969, 89-A) according to this law a bike ride should have to wear a helmet before riding a bike. Nowadays this law is imposed on the public by the traffic police manually. A traffic cop sees a person not wearing a helmet and fine (1,000) him according to the rule. But there is an issue that some persons may not be detected by him and some persons may run away. To resolve this issue we will work on automated helmet detection by road cameras and impose a fine on a person violating the rule automatically by detecting his face.

Project Implementation Method

The system will work on the following operating environments. Python: python language will be used to build this system. the programming of the system will be done with a python programming language Yolo: Yolo is a real-time object detection software that will be used in our system. Our base YOLO model processes images in real-time at 45 frames per second. A smaller version of the network, Fast YOLO, processes an astounding 155 frames per second while still achieving double the map of other real-time detectors. Compared to state-of-the-art detection systems, YOLO makes more localization errors but is far less likely to predict false detections where nothing exists. Finally, YOLO learns very general representations of objects. It outperforms all other detection methods, including DPM and R-CNN, by a wide margin when generalizing from natural images to artwork on both the Picasso Dataset and the People-Art Dataset. Google colab: Colaboratory, or' Colab' for short, is a Google Research product. Colab enables anybody through the browser to write and execute arbitrary python code and is specifically well suited to computer learning, data processing, and education. More technically, Colab is a hosted Jupyter notebook service that does not require any modification to use while offering free access to device resources, including GPUs.

Benefits of the Project

As day by day, most bike riders cause serious injuries. To save these type of serious issue Government impose some rules on the public like as helmet wearing law(PMVO 1969, 89-A) according to this law a bike ride should have to wear a helmet before riding a bike. Nowadays this law is imposed on the public by the traffic police manually. A traffic cop sees a person not wearing a helmet and fine (1,000) him according to the rule. But there is an issue that some persons may not be detected by him and some persons may run away. To resolve this issue we will work on automated helmet detection by road cameras and impose a fine on a person violating the rule automatically by detecting his face.

Technical Details of Final Deliverable

A computer on which the software is installed must have a good graphic card (GTX780) ram of 6 GB and a good processor (any core series). We should need to install dark net weights and Yolo algorithm files Page 5 of 8 on the operating machine and python SQL database all are required to run this software. Also required a good resolution camera for detecting the persons on roads

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People, Decent Work and Economic Growth

Required Resources

Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
Camera Equipment15000050000
Miscellaneous Cost Miscellaneous 11000010000
Total in (Rs) 60000
If you need this project, please contact me on contact@adikhanofficial.com
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