Driving Negligence Dissuader

Project Title

Driving Negligence Dissuader

Project Area of Specialization Artificial IntelligenceProject Summary

Road traffic injuries cause considerable economic losses to individuals, their families, and to nations as a whole. These losses arise from the cost of treatment as well as lost productivity for those killed or disabled by their injuries, and for family members who need to take time off work or school to care for the injured. Road traffic crashes cost most countries 3% of their gross domestic product.[1] Every year the lives of approximately 1.3 million people are cut short as a result of a road traffic crash. Between 20 and 50 million more people suffer non-fatal injuries, with many incurring a disability as a result of their injury.[2] The National Highway Transportation Safety Administration (NHTSA) found that somewhere between 94% and 96% of all motor vehicle accidents are caused by some type of human error.[3] According to the National Sleep Foundation, 41% of drivers surveyed admitted that they have fallen asleep at the wheel at some point in their lives, and 10% reported that they have done it in the past year. In this paper, an IoT-based intelligent system is proposed that uses computer vision to recognize the driver’s facial features and behaviour and Alarm or notify the driver to be more attentive and careful in case of negligence.

Project Objectives

1. The above-proposed project will accomplish the following goals.

   • Reduce human casualties and injuries due to road accidents caused by drivers’ negligence by providing organizations and individuals with a system to monitor drivers’ behaviour.

   • Increase the quality of driving and road safety by alerting and notifying drivers as they feel drowsy or distracted, while also alerting them if they stay outside their lane for longer than usual or warning them to slow down if the system detects pedestrians up ahead.

   • Monitor drivers’ behaviour and performance by saving logs and dashcam footage for the organization and users to review later.

Project Implementation Method

To implement the project proposes above we start with a camera module and an alarm integrated with the application, it continuously records each movement of the driver’s face. This proposed work will focus on behavioural measures of the driver. The camera modules make a persistent recording of face landmarks that are localized through facial landmark points in order to detect drowsiness and distraction. Upon detecting drowsiness or lack of attention the alarm system warns the driver in real-time while also saving the instance of this trigger in the logs. Another camera module is integrated that is dedicated to detecting lanes and pedestrians. It also records the road ap ahead. In case of any mishap, the recorded footage and logs stored can be used to analyze and review the situation. The above modules are properly integrated with each other and controlled by a single application.

Benefits of the Project

The above-proposed systems could solve the drowsiness problem in particular. However, the system can be improved further by adding functionality and features.

• Add lane detection to make sure driver is staying on their lane.

• Adding pedestrian detection feature.

• Monitoring driver’s behaviour and making sure the driver is not distracted. (Using

  smartphone, Not paying attention to the road etc).

• Add dashcam to record the entire driving session for legal reasons.

• Adding logs saving functionality for the user or organization to review.

Technical Details of Final Deliverable

Some datasets and libraries are required in order to develop the proposed system. The necessary equipment required to complete this project is

• Laptop computer

• Raspberry Pi3 Model B

• Pi camera module v2

• Speaker Module

• PyCharm Professional edition IDE

• MATLAB for Image Processing and Computer Vision

  Acquiring the above equipment and necessities should set us back about RS.70,000-80,000/- PKR.

• The above-proposed systems could solve the drowsiness problem in particular. However, the system can be improved further by adding functionality and features.

• Add lane detection to make sure driver is staying in their lane.

• Adding pedestrian detection feature.

• Monitoring driver’s behaviour and making sure the driver is not distracted. (Using

  smartphone, Not paying attention to the road etc).

• Add dashcam to record the entire driving session for legal reasons.

• Adding logs saving functionality for the user or organization to review.

Final Deliverable of the Project HW/SW integrated systemCore Industry OthersOther Industries IT , Legal , Transportation , Health , Security Core Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT), OthersSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	65000
Raspberry Pi3 model B	Equipment	1	30000	30000
Pi camera module v2	Equipment	3	10000	30000
Raspberry pi Speaker Module	Equipment	1	5000	5000