Check patentability & draft patents in minutes with Patsnap Eureka AI!

Python-based dangerous drive warning system

An early warning system and dangerous driving technology, applied in the fields of instruments, electrical digital data processing, creation/generation of source codes, etc., can solve the problems of inability to make accurate early warnings, the types of detection are not wide enough, and the early warning system is not concise enough. The effect of reducing the burden on the algorithm, widening the function and improving the efficiency

Inactive Publication Date: 2018-12-21
HUAIHAI INST OF TECH
View PDF1 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Therefore, safety warning for driving is essential, and an early warning system for driving safety warning is needed. The current early warning system is not simple enough, and the types of detection are not wide enough to make accurate early warning.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Python-based dangerous drive warning system
  • Python-based dangerous drive warning system
  • Python-based dangerous drive warning system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0063] see Figure 1-Figure 6 As shown, the technical solution adopted in this specific embodiment is: it includes seat belt detection, fatigue driving detection, and hand-held phone call behavior detection. The seat belt detection is mainly to process, detect, and identify the pictures acquired by the camera. One is the seat belt detection method based on Hough transform, which calculates the similar parallel, spacing, and slope of straight lines; the second is the approximate belt shape detection method, which calculates the distance between edge pixel points and the slope between multiple points; The fatigue driving detection mainly performs facial landmark detection through the built-in face detector of Dlib to the video captured by the camera, and detects the eye-closing action in the video; Construct a classifier trained by a convolutional neural network to classify images.

[0064] A dangerous driving warning system based on Python which includes the following steps: ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

A Python-based dangerous drive warning system relates to the field of dangerous driving warning. The invention comprises a seat belt detection, a fatigue driving detection, and a handheld telephone behavior detection, wherein the seat belt detection is a seat belt detection method based on a Hough transform; The second method is approximate band shape detection. The fatigue driving detection mainly performs facial mark detection on the video captured by the camera through a face detector built in the Dlib, and detects the eye closing action in the video; The hand-held telephone behavior detection mainly comprises classifying pictures obtained by the camera through a classifier trained by a convolution neural network constructed by Keras. The invention has the beneficial effects that the system is more concise and fast by using PyCharm, and can detect more detection and wider function for seat belt detection, fatigue driving detection and handheld telephone behavior detection, and the combination of a plurality of detection methods makes the safety detection more accurate and diversified.

Description

technical field [0001] The invention relates to the field of dangerous driving early warning, in particular to a Python-based dangerous driving early warning system. Background technique [0002] According to Article 133 of the "Criminal Law of the People's Republic of China", the crime of dangerous driving refers to driving a motor vehicle on the road: chasing and racing, the circumstances are serious; driving a motor vehicle while drunk; engaging in school bus business or passenger transportation, serious Carrying more passengers than the quota, or seriously exceeding the prescribed speed; transporting hazardous chemicals in violation of the regulations on the safety management of hazardous chemicals, endangering public safety. [0003] In 2010, the National "Two Sessions" proposed "Suggestions on Increasing the Crime of Dangerous Driving", suggesting that the criminal law add "crime of dangerous driving". Let "dangerous driving" be a "crime", dangerous driving behavior, ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06F8/30
CPCG06F8/315
Inventor 汪前进郑占杰
Owner HUAIHAI INST OF TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com