Project owner's name :
Mr Emad Ahmed
Mr Emad Ahmed
Country of deployment for the project :
Egypt
Egypt
Sector :
Health
Health
What problem does your company want to solve? :
Drowsy or distracted driving can put lives of many drivers and workers in danger. By implementing effective detection systems, road safety can be improved.
Drowsy or distracted driving can put lives of many drivers and workers in danger. By implementing effective detection systems, road safety can be improved.
What solution does your company provide? :
Enhance road safety: The project aims to contribute to road safety by providing an effective tool for identifying drowsy drivers. By accurately detecting drowsiness, the system can alert drivers also.
Enhance road safety: The project aims to contribute to road safety by providing an effective tool for identifying drowsy drivers. By accurately detecting drowsiness, the system can alert drivers also.
Describe your project :
The "Smart Drowsiness Detection System for Safer Driving with Multi-Level Alerts and V2N/V2V Integration" project is aiming to develop an innovative solution to combat the pressing issue of drowsy driving. This project will create a comprehensive system that combines advanced sensor technology and deep learning algorithms to monitor the driver's state in real-time. Furthermore, it integrates multi-level alert mechanisms (Visual, auditory and sensory) and V2N (Vehicle-to-Network) and V2V (Vehicle-to-Vehicle) communication technologies to enhance driver safety and address emergency situations. The proposed system will not only reduce drowsy driving-related accidents but also play a crucial role in emergency scenarios by communicating with other vehicles and emergency services.
The "Smart Drowsiness Detection System for Safer Driving with Multi-Level Alerts and V2N/V2V Integration" project is aiming to develop an innovative solution to combat the pressing issue of drowsy driving. This project will create a comprehensive system that combines advanced sensor technology and deep learning algorithms to monitor the driver's state in real-time. Furthermore, it integrates multi-level alert mechanisms (Visual, auditory and sensory) and V2N (Vehicle-to-Network) and V2V (Vehicle-to-Vehicle) communication technologies to enhance driver safety and address emergency situations. The proposed system will not only reduce drowsy driving-related accidents but also play a crucial role in emergency scenarios by communicating with other vehicles and emergency services.