Globally, driver drowsiness plays a major role in traffic accidents. In order to tackle this problem, we introduce the development and deployment of an Anti-Sleep Alarm System (ASAS) with the goal of averting sleep-related driving accidents. In order to identify indicators of weariness and send out appropriate notifications, this study presents a novel method that blends sophisticated signal processing techniques with real-time physiological signal monitoring of drivers. This system is designed to be comfortable and convenient for prolonged usage, utilising a wearable gadget that is integrated into a driver's headset. Worldwide, one of the main causes of road accidents is fatigued drivers. To address this issue, we propose the creation and implementation of an Anti-Sleep Alarm System (ASAS) with the intention of preventing driving accidents caused by sleepiness. This work proposes a novel approach that combines advanced signal processing techniques with real-time physiological signal monitoring of drivers to detect signs of exhaustion and give out relevant messages. Fatigued drivers are a major contributing factor in traffic accidents worldwide. In order to reduce sleepiness-related driving accidents, we suggest developing and implementing an Anti-Sleep Alarm System (ASAS) as a solution to this problem. In order to identify indicators of fatigue and deliver pertinent instructions, this work suggests a novel method that blends cutting-edge signal processing techniques with real-time physiological signal monitoring of drivers.


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    Title :

    Enhanced Driver Safety: IoT Based Anti-Sleep Alarm and Automatic Braking System Using Eye Blink Sensor


    Contributors:


    Publication date :

    2024-12-19


    Size :

    279036 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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