Driver Drowsiness Detection System Based on Raspberry Pi Using Convolutional Neural Network (CNN)
This paper describes the implementation of a Raspberry Pi-based system for detecting drowsy driving. Drowsy driving is characterised by a decline in driving skills. The Convolutional Neural Network (CNN) was used to classify drowsiness symptoms such as blinking and yawning in this study. 1310 images were utilised during CNN architecture training
1.5) Raspberry Pi-Based Face Recognition Door Lock
Extensive research is conducted in the field of home security, which is the turning point of the industry, where we connect common items to share data for our development.
1.6) Camera-based Fire Detection System Employing Raspberry Pi
The risk of fire hazards has also increased significantly, causing a great deal of damage to nature, lives, and property and resulting in a massive economic loss. A camera-based fire alert system will be immensely helpful in detecting fires in commercial buildings, industries, establishments, and public places in order to reduce and eventually eliminate fire accidents.
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2. Top and latest Arduino-based projects for ECE
