Stay Alert: Drowsiness Detection with IoT Technology

,. C. G. K. C. G Sudha Rani, A Anusha, A Yamini, I.Srinivasa Rao
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Abstract

The "Drowsiness Detection using IoT with Eye Blink Sensor and Buzzer" project aims to address the critical issue of driver fatigue and drowsiness, a major cause of road accidents. Leveraging Internet of Things (IoT) technologies and a combination of eye blink sensors and a buzzer, this system provides a real-time solution for monitoring and alerting drivers when signs of drowsiness are detected. The project focuses on enhancing road safety by preventing accidents caused by driver fatigue Drowsiness detection is a critical aspect of ensuring safety, particularly in domains such as transportation where fatigue-related accidents pose significant risks. In recent years, the proliferation of Internet of Things (IoT) devices has enabled innovative approaches to drowsiness detection systems. This abstract outlines a novel framework for drowsiness detection utilizing IoT technologies. Our proposed system integrates various sensors, including facial recognition cameras, heart rate monitors, and accelerometers, into a networked IoT infrastructure. These sensors continuously monitor key physiological and behavioral indicators associated with drowsiness, such as eye movement patterns, blink frequency, heart rate variability, and head position changes.
保持警惕:利用物联网技术进行瞌睡检测
利用眨眼传感器和蜂鸣器的物联网进行瞌睡检测 "项目旨在解决驾驶员疲劳和瞌睡这一严重问题,这是造成道路交通事故的主要原因。利用物联网(IoT)技术以及眨眼传感器和蜂鸣器的组合,该系统提供了一种实时解决方案,可在检测到司机有瞌睡迹象时对其进行监控并发出警报。该项目侧重于通过预防驾驶员疲劳导致的事故来提高道路安全。 嗜睡检测是确保安全的一个重要方面,尤其是在交通等领域,疲劳相关事故会带来巨大风险。近年来,物联网(IoT)设备的普及为嗜睡检测系统提供了创新方法。本摘要概述了一种利用物联网技术进行瞌睡检测的新型框架。我们提出的系统将面部识别摄像头、心率监测器和加速度计等各种传感器集成到联网的物联网基础设施中。这些传感器可持续监测与瞌睡相关的关键生理和行为指标,如眼球运动模式、眨眼频率、心率变异性和头部位置变化。
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