PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 24, 2026Iconic Research and Engineering Journals0 citations

DROWZISHIELD: An AI-Based Real-Time Driver Drowsiness and Pedestrian Detection System

AKAditya KharadeSSSarthak ShindeSWSarvesh Wani

Key Points

  • The aim is to develop a system that uses AI to monitor driver fatigue and pedestrian presence to enhance overall road safety.
  • Developed an AI system utilizing computer vision techniques for real-time monitoring
  • Monitors facial features to detect driver drowsiness
  • Analyzes road environment to identify pedestrians using object detection models
  • Successfully detects driver drowsiness and pedestrian presence in real time
  • Generates alerts when risky situations are identified
  • Improves driver awareness and reduces potential accidents

Abstract

Road accidents caused by driver fatigue and pedestrian collisions are a major concern worldwide. Drivers often become drowsy during long journeys, which reduces their concentration and reaction time, increasing the risk of accidents. Pedestrians are also among the most vulnerable road users and are often involved in road accidents due to delayed driver response. The proposed system, DROWZISHIELD, is an AI-based safety system that detects driver drowsiness and pedestrians in real time using computer vision techniques. The system monitors the driver's facial features to detect fatigue and simultaneously analyzes the road environment to identify pedestrians using object detection models. When the system detects a risky situation, it generates alerts to warn the driver. This approach enhances road safety by improving driver awareness and preventing potential accidents.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Kharade et al. (2026) studied this question.

synapsesocial.com/papers/69eb0bc7553a5433e34b5576https://doi.org/10.64388/irev9i10-1716602
Ask AI
Helpful
Bookmark
Share
View Full Paper