Drowsiness

DRIVER DROWSINESS
DETECTION SYSTEM
TEAM MEMBERS:
 ANKITHA P
 DHANUSH B M
 DEEPAK NAYAKA N
 MOHAMMED FURQAN
 MANOJ N M
 RUCHITHA N S
 SUSHMITHA R K
INTRODUCTION:
 Drowsiness is the state of feeling tired or sleepy. We all can be victim of drowsiness while driving,
simply after too short night sleep, tired physical condition or during long journey.
 Driver fatigue affects the driving ability in the following 3 areas:
 It impairs coordination
 It causes longer reaction times and,
 It impairs judgment
 A drowsy driver detection system has been developed to concentrate the eyes of driver and check the
drowsiness.
PROBLEM STATEMENT:
 Real-Time Driver Drowsiness Detection System Based on Visual Information.

The aim is to provide a driver drowsiness detection system which will alert not only the driver
but also the co-passengers when the driver is drowsy with a loud alarm in the vehicle. Real
time data is collected by the web-camera. For that we will be using face tracking and video
processing. This data gives information about the driving condition of the driver which acts as
the input for the system.
PROBLEM SOLUTION:
 Our aim is to provide a driver drowsiness system which will alert not only the driver but also
the co-passengers with a loud alarm in the car
 To accurately identify drowsiness of the driver
 On successful detection, alert the user with a loud beep
 Detection in real-time is the major challenge in the field of accident prevention system. The
purpose of this project is to provide a real-time monitoring system using video processing,
face/eye detection techniques. This project deals with automatic driver drowsiness detection
based on visual information. Our project will capture the video through camera and after
processing, it will alert the driver based on the results.
MARKET POTENTIAL:
 Our current statistics reveal that just in 2015 in India alone, 148,707 people died due to car
related accidents.
 Of these, at least 21% were caused due to fatigue causing drivers to make mistakes. This
can be a relatively smaller number still, as among the multiple causes that can lead to an
accident, the involvement of fatigue as a cause is generally grossly underestimated.
 Shocking statistics revealed by World Health Organization (WHO) in a 2009 report
showed that more than 1.2 million people die on roads around the world every year.
Moreover, an additional 20 to 50 million individuals suffer non-fatal injuries. 100,000
crashes per year (i.e., 1.6% of 6.3 million) were identified with drowsiness in the
corresponding Police Crash Reports (PCR). Additionally, many other accident reports
referred to Drift-Out-Of-Lane crashes, which might be related to drowsiness aspects as
well. Approximately 71,000 of all drowsy-related crashes involved non-fatal injuries,
whereas 1,357 drowsy-related fatal crashes resulted in 1,544 fatalities (3.6%of all fatal
crashes), as reported by the Fatality Analysis Reporting System (FARS).
CUSTOMER ACQUISITION STRATEGY:
Acquiring customers for a driver drowsiness detection system involves understanding the target market, creating awareness, and
providing value to potential users. Here's a comprehensive customer acquisition strategy for a driver drowsiness detection system:
1. Market Research:
- Identify the target audience: Determine the demographics and psychographics of the potential users. This may include long-haul truck
drivers, delivery drivers, fleet managers, and regular commuters.
2. Build a Comprehensive Product Offering:
- Develop a reliable and user-friendly driver drowsiness detection system that meets industry standards.
3. Create an Online Presence:
- Develop a professional website with detailed information about the product, its features, benefits, and use cases.
- Utilize social media platforms to share information, engage with the audience, and build a community.
4. Content Marketing:
- Develop content that educates users about the dangers of driver drowsiness and the benefits of your solution.
- Create blog posts, articles, infographics, and videos that highlight the importance of staying alert while driving.
5. Partnerships and Collaborations:
- Collaborate with automotive manufacturers, fleet management companies, and insurance providers to integrate your solution into
their systems.
- Form partnerships with driver safety organizations and participate in industry events to enhance credibility.
6. Targeted Advertising:
- Use online advertising platforms such as Google Ads and social media ads to target specific demographics.
- Run campaigns emphasizing the safety benefits of your drowsiness detection system.
7. Free Trials and Demos:
- Offer free trials or demos to potential customers to let them experience the effectiveness of your product.
- Gather feedback and testimonials from trial users to build credibility.
8. Influencer Marketing:
- Partner with influencers in the automotive and safety industry to promote your product.
- Influencers can provide authentic reviews and demonstrations to a wider audience.
9. Customer Support and Engagement:
- Provide excellent customer support to address queries and concerns promptly.
- Encourage user engagement through forums, social media groups, and feedback sessions.
10. Educational Webinars and Workshops:
- Conduct webinars or workshops to educate potential customers about the risks of driver drowsiness and how
your solution can mitigate these risks.
11. Referral Programs:
- Implement referral programs to incentivize existing customers to refer your product to others.
- Offer discounts, extended trials, or other rewards for successful referrals.
12. Regulatory Compliance:
- Ensure that your product complies with relevant safety and regulatory standards, and communicate this
compliance in your marketing materials.
BUSINESS MODEL:
 This project uses a video camera for image acquisition and rely on a combination of computer vision
and machine learning techniques to detect events of interest, measure them, and make a decision on
whether the driver may be drowsy or not. If the sequence of captured images and measured parameters
suggest that the driver is drowsy, an action (such as sounding an alarm) might be warranted.
 Driver drowsiness detection systems based on visual input are specialized computer vision solutions,
which capture successive video frames, process each frame, and make decisions based on the analysis of
the processed information. After capturing each frame using an imaging sensor one or more feature
detection and extraction algorithms are applied to the pixel data.
 Any system designed to monitor the state of an object of interest over time must be capable of
detecting that object, determining what state the object is in, and tracking its movements.
 In the specific case of driver drowsiness detection system whose goal is to determine the
drowsiness state of a driver by observing the driver's facial features, the focus is on the head,
face, and eyes.
 A successful driver drowsiness detection system must be fast, robust, reliable, nonintrusive and
proactive. The ultimate goal of such systems is to work in a real world, which means that the
system should reach conclusive decisions about the state of the driver (and the need to issue an
alert) in a timely manner.
FINANCIAL PROJECTIONS:
 As you can see in the graph , the sales of all kinds of vehicles sales in India is shown. Our target
would be gather the attention of all the vehicles manufacturing companies to look forward in the
product and implement in their vehicles during manufacturing so that these features would be pre
installed in the vehicles to avoid any further disruption.
 Driver Drowsiness Detection System helps to reduce fatal accidents in all kinds of vehicles
moving on road.
ADVANTAGES:
 Prevent Accidents: Drowsiness is one of the leading causes of road accidents.
 Improve Driver Safety: Drowsiness can affect a driver's ability to make decisions, react
quickly, and stay focused on the road.
 Reduce Driver Fatigue: Long hours of driving can be tiring, and drowsiness can result in
decreased productivity and an increased risk of accidents.
LIMITATIONS:
 False Alarms: Some drowsiness detection systems may generate false alarms due to some
factors
 Reliance on Technology: Drowsiness detection systems rely on technology, which can

malfunction or fail.
 Cost: Drowsiness detection systems can be expensive, especially high-end models with
advanced features.
TEAM BACKGROUND:
 We are the students of Siddaganga Institute of Technology, Tumkur pursuing Civil
Engineering and currently in 3rd Year.
 FOUNDER: Deepak Nayaka N

 CO-FOUNDER: Manoj N M
 Our team includes :

o ANKITHA P : MARKETING HEAD
o MOHAMMED FURQAN : PRODUCTION HEAD
o SUSHMITHA R K : QUALITY CHECK HEAD
o RUCHITHA N S : STOCK MANAGEMENT HEAD
o DHANUSH B M : DELIVERY & TRANSPORTATION HEAD
KEY MILESTONES:
 There is a strong growth for the Driver Drowsiness Detection System Market as the technology
improves and becomes more ubiquitous. Key developments on the horizon include:
 More widespread adoption of driver monitoring systems
 Enhanced sensor fusion and accuracy
 Customizable alert intensities and driver feedback
 Integration with semi-autonomous vehicle technologies
 Development of standardized metrics and testing
 Mandates by regulatory bodies for commercial vehicles
 Drowsy driving presents a major risk on our roadways, contributing to thousands of crashes
each year. As driver drowsiness detection systems continue to evolve, they have tremendous
life-saving potential if implemented properly. With future improvements in accuracy,
affordability and seamless integration, these technologies could play a key role in reducing
fatigue-related accidents and making driving safer for everyone.
FUNDING NEEDS & USES:
 The production of one unit of drowsiness detection system would cost somewhere around Rs 25,000.
To begin with we would produce about 1000 units which would cost about Rs 2,50,00,000.
 The Funds required would be about Rs 5,00,00,000
 The breakdown in the funds would be as follows:
• Production Cost : Rs 2,00,00,000
• Machinery Cost : Rs 80,00,000
• Labour Cost : Rs 65,00,000
• Transportation Cost : Rs 20,00,000
• Miscellaneous Cost : Rs 10,00,000
• Land Rent Cost : Rs 15,00,000
• Manufacturing Unit Cost : Rs 15,00,000
• Government Taxes Cost : Rs 10,00,000
• Advertisement Cost : Rs 5,00,000
• Reserve Amount : Rs 80,00,000
 PROJECTED ROI is estimated to be around Rs 50,00,000.

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DRIVER DROWSINESS

 Real-Time Driver Drowsiness Detection System Based on Visual Information.

 Prevent Accidents: Drowsiness is one of the leading causes of road accidents.

 Reliance on Technology: Drowsiness detection systems rely on technology, which can

 FOUNDER: Deepak Nayaka N

 Our team includes :

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