There has been a significant increase in road and rail accidents owing to driver drowsiness, which results in massive deadly incidents. When the driver falls asleep, he loses control, resulting in an accident. People know that driving while drowsy is dangerous, but they may not know how to detect their own level of sleepiness. The proposed solution will provide you with information on how to look for signs of potential driver drowsiness and take appropriate action. The existing methods are classified into three primary categories: vehicular-based, behavioral-based, and physiological-based. The main aim of this research is to design a real-time smart alert system for the prevention of vehicle accidents and a fire system for intelligent vehicles that spontaneously can avoid drowsy driver loss. The necessity of an anti-sleep alarm system is increasing day by day to curb the misfortune. In this study, we have developed an anti-sleep alarm device through IoT. Here the alarm will be activated automatically if a driver falls asleep for more than 2 s during the driving of a vehicle. The vehicle engine will stop automatically in the case of sleepiness of the driver exceeds 5 s. Moreover, an auto “fire alarm System” was also established to prevent accidents due to fire in the vehicle. Here the fire alarm will be activated automatically in case of the occurrence of fire. An emergency phone no is attached to the system for sending the messages related to fire detection where the vehicle owner will be informed about the incident and take the necessary steps in this regard.
Real-Time Smart Alert System for Prevention of Vehicle Accident and Fire: An IoT-Based Alarm System
Lect. Notes in Networks, Syst.
International Conference on Innovations in Data Analytics ; 2023 ; Kolkata, India November 29, 2023 - November 30, 2023
21.07.2024
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Driver safety , Anti-sleep alarm system , Drowsiness detection , Fire alarm system , Early warning , Accident prevention Engineering , Computational Intelligence , Statistics, general , Computer Imaging, Vision, Pattern Recognition and Graphics , Systems and Data Security , Communications Engineering, Networks
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