How This Startup Using Object Detection For Safer Driving
Table of Contents
Introduction
The problem of real-time object detection for safer driving affects the transportation industry and any other industries that rely on vehicles for their operations. The problem is that distracted or impaired driving can lead to accidents, injuries, and even fatalities.
Real-time object detection can help to reduce the number of accidents caused by distracted or impaired driving by alerting drivers to potential hazards on the road.
Transportation is one of the world's largest and most critical industries, moving people and goods across vast distances. However, road safety has become a significant challenge with the transportation industry's growth.
Distracted and impaired driving is a major contributor to road accidents, which causes loss of life and injury and result in significant economic losses in terms of property damage, healthcare costs, and loss of productivity.
Figure: Detecting obstacles using Computer vision
The problem of distracted or impaired driving is a significant one that affects millions of people worldwide. According to the World Health Organization (WHO), road traffic accidents cause 1.35 million fatalities and 50 million injuries yearly. The cost of these accidents is also significant, with estimates suggesting that it can cost countries up to 4% of their GDP.
In the United States, the National Highway Traffic Safety Administration (NHTSA) reports that distracted driving was responsible for over 3,000 deaths in 2019. According to a study by the National Safety Council, the cost of motor vehicle crashes in the United States was over $433 billion in 2019. These costs include medical expenses, property damage, and lost productivity.
Role of Computer Vision
Computer vision can solve the problem of real-time object detection for safer driving by using cameras and sensors to capture real-time video feeds of the road and surrounding environment.
Computer vision algorithms can then analyze these feeds to identify potential hazards like pedestrians, other vehicles, or obstacles. The system can then provide drivers with alerts and warnings to avoid potential hazards or take corrective actions.
Computer vision algorithms can also analyze data from other sources, such as weather and traffic information, to provide drivers with information about road conditions and potential hazards.
One such company which utilizes real-time object detection for a safer driving experience for users is Nauto.
About Nauto
Nauto is a company that provides an AI-powered driver safety system for commercial fleets. The system uses real-time object detection to help drivers avoid potential hazards on the road and improve their driving behaviors.
Figure: Nauto’s Webpage
Nauto's system uses a combination of cameras, sensors, and artificial intelligence algorithms to analyze the driver's behavior and the surrounding environment. The system can detect and recognize various objects, including pedestrians, other vehicles, and road signs.
One of the critical features of Nauto's system is its ability to provide real-time alerts to drivers. For example, suppose the system detects that the driver is not paying attention to the road or is about to collide with another vehicle. In that case, it will provide the driver an audible and visual alert. The system can also detect potential hazards, such as pedestrians or obstacles in the road, and alert the driver.
Founders
Nauto is a Silicon Valley-based company founded in 2015 by Stefan Heck, Fredrik Ö̈stbye, and Shiv Sikand. The company develops AI-powered vehicle technology that can help prevent collisions and improve fleet safety.
Stefan Heck, one of the co-founders, is a sustainability expert, entrepreneur, and author. Before starting Nauto, he was the CEO of McKinsey's Cleantech Practice and authored the book "Resource Revolution: How to Capture the Biggest Business Opportunity in a Century."
Fredrik Ö̈stbye, another co-founder, is an experienced software engineer and entrepreneur. Before co-founding Nauto, he worked as a senior software engineer and tech lead for various projects at Google.
Shiv Sikand, the third co-founder, is a product and business development expert with experience in the automotive industry. Before co-founding Nauto, he worked at Ford Motor Company for over a decade and held various product development and strategy roles.
Together, the three co-founders bring unique skills and experiences to Nauto. Their goal is to use technology to make driving safer and more efficient. They have developed AI-powered cameras and sensors to detect risky behavior and provide drivers and fleet managers with real-time alerts. The company has raised over $170 million in funding and has partnerships with several major companies in the automotive and transportation industries.
How Nauto uses Computer Vision
Nauto employs computer vision to increase fleet safety and lower the number of collisions brought on by unsafe or distracted driving. The company's AI-powered cameras and sensors are intended to identify unsafe conduct and provide drivers and fleet management with immediate notifications.
The cameras, installed on a car's windscreen, employ computer vision algorithms to scan the surrounding area for other vehicles, people walking by, and road signs. The cameras can notify drivers of unsafe driving habits like aggressive, sleepy, and distracted driving.
The cameras also record mishaps or accidents on video, allowing for investigation and cause-and-effect analysis.
Machine learning algorithms underpin Nauto's technology, which can analyze massive volumes of data and provide fleet management insights. To help drivers and fleet managers improve their driving practices and lower the risk of accidents, the algorithms can spot patterns of unsafe conduct and give feedback.
Overall, Nauto's application of computer vision technology has the potential to greatly enhance the security of commercial fleets and lower the frequency of collisions brought on by unsafe or distracted driving.
Figure: Features provided by Nauto
Nauto's system also includes a "Coaching" feature, which gives drivers feedback on their driving behaviors. The system can detect and analyze data on factors such as speeding, harsh braking, and sudden acceleration and provide recommendations to drivers on improving their driving behaviors.
In addition to its safety features, Nauto's system includes a fleet management platform that provides data and analytics on driver behavior and vehicle performance. The platform can help fleet managers optimize routes, reduce fuel consumption, and improve fleet efficiency.
Overall, Nauto's use of real-time object detection is designed to improve driver safety and reduce the risk of accidents on the road. By providing real-time alerts and feedback to drivers, the system can help them make better decisions and avoid potential hazards, ultimately improving the safety of everyone on the road.
Conclusion
Real-time object detection can significantly reduce the number of accidents caused by distracted or impaired driving by alerting drivers to potential hazards on the road.
Transportation is one of the world's largest and most critical industries, moving people and goods across vast distances. Still, road safety has become a significant challenge with the transportation industry's growth.
Computer vision can solve the problem of real-time object detection for safer driving by using cameras and sensors to capture real-time video feeds of the road and surrounding environment. Computer vision algorithms can then analyze these feeds to identify potential hazards like pedestrians, other vehicles, or obstacles.
One such company that utilizes real-time object detection for a safer driving experience is Nauto.
Nauto is a company that provides an AI-powered driver safety system for commercial fleets. The system uses real-time object detection to help drivers avoid potential hazards on the road and improve their driving behaviors.
Nauto employs computer vision to increase fleet safety and lower the number of collisions brought on by unsafe or distracted driving. The company's AI-powered cameras and sensors are intended to identify unsafe conduct and provide drivers and fleet management with immediate notifications.
Nauto's system also includes a "Coaching" feature, which gives drivers feedback on their driving behaviors. The system can detect and analyze data on factors such as speeding, harsh braking, and sudden acceleration and provide recommendations to drivers on improving their driving behaviors.
Read our tutorial blog on "Create Object Detection Model Using Python & Open CV" to build custom model on your own.