Helmet Detection

Project Title

Helmet Detection

Project Area of Specialization Artificial IntelligenceProject 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 SystemCore Industry ITOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Good Health and Well-Being for People, Decent Work and Economic GrowthRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	60000
Camera	Equipment	1	50000	50000
Miscellaneous Cost	Miscellaneous	1	10000	10000