Smart Accident Preventing System by using CNN

Project Title

Project Area of Specialization

Artificial Intelligence

Project Summary

In the current scenario one of the major causes of road accidents in the world is the fact that after driving hundreds of kilometers at a stretch, the driver feels drowsy and eventually dozes off while driving they are not giving attention while they are driving like usage of mobile phones. They are not aware of the environment they might just be entering. So, there is a pressing need of a device which prevents this, so that a lot of lives can be saved every day. Safety is the primary concern for humans. When it comes to driving, we need to be extra cautious. So, this project aims at developing an affordable solution to these safety concerns. The proposed system will be mounted on a car, in front of the driver's seat, which will continuously focus on the person driving the vehicle thereby monitoring the person's actions and If he found to be drowsy, he is alerted by shaking/vibrating telling him that he is drowsy or If he is found to be under the influence of alcohol. There is a camera attached on the front which is interfaced with Raspberry Pi. The camera is monitoring the driver’s condition and if the conditions of the driver is as above then the Raspberry Pi will instruct the vibration layer to vibrate which is placed under the driver’s seat to vibrate. So, this system has the capability of ensuring the driver's safety along with the co-passengers and can easily be integrated with the existing safety systems in the car. In future, it can be enforced by law for every car to have such a safety system installed for driver and passenger protection. Hence the system is a complete solution which prevents accidents, so that a lot of lives can be saved every day.

Project Objectives

To prevent accidents caused by the drowsiness (unconsciousness) of driver.
To install a new smart system for safety.
To ensure the driver’s safety along passenger’s.

Project Implementation Method

In the project, we will attach a camera in front of the driver. The camera is interfaced with Raspberry Pi. There is a vibration layer placed under the driver’s seat and is connected to Raspberry Pi. The camera will monitor the driver’s condition continuously. When the driver’s feels tired, drowsy and took his/her eyes off the road then Raspberry pi will instruct the vibration layer to vibrate. The whole project is based on CNN (Convolutional Neural Network). We will create a dataset in which all the possible data will be stored.

Benefits of the Project

The most important advantage that a Smart Accident Preventing System will bring to the table is an enhanced sense of safety. This isn’t just crucial for your driver; it’s crucial for pedestrians, bicyclists, and other drivers on the road as well. When you use a collision avoidance system, you can rely on your technology to prevent accidents from occurring. This keeps everybody safe, prevents damage to company vehicles, and ensures that the driver stays on track.

Technical Details of Final Deliverable

It is a hardware/software integrated project . The camera and vibration layer is interfaced with the Raspberry Pi which is running on CNN classifier. The camera monitors the driver’s condition and sends the data to Raspberry Pi continuously . When the driver is tired, drowsy and and took his/her eyes off the road then Raspberry pi will instruct the vibration layer to vibrate. The whole project is based on CNN (Convolutional Neural Network). We will create a dataset in which all the possible data will be stored.