scholarly journals Detection of Driver Drowsiness using Eye Blink Sensor

2018 ◽  
Vol 7 (3.12) ◽  
pp. 498 ◽  
Author(s):  
Kusuma Kumari B.M ◽  
Sampada Sethi ◽  
Ramakanth Kumar P ◽  
Nishant Kumar ◽  
Atulit Shankar
Keyword(s):  
Wheel Speed ◽  
Vibration Sensor ◽  
Police Station ◽  
Eye Blink ◽  
Driver Drowsiness ◽  
Warning Messages ◽  
Lcd Displays

Accidents due to driver drowsiness can be prevented using eye blink sensors. The driver is supposed to wear the eye blink sensor frame throughout the course of driving and blink has to be for a couple of seconds to detect drowsiness. Any random changes in steering movement leads to reduction in wheel speed. The threshold of the vibration sensor can be varied and accordingly action can be taken. The outcome is that the vibrator attached to eye blink sensor’s frame vibrates if the driver falls asleep and also the LCD displays the warning messages. The wheel is slowed or stopped depending on the condition. This is accompanied by the owner being notified through the GSM module, so the owner can retrieve the driver’s location, photograph and police station list near to driver’s location. This is how the driver can be alerted during drowsiness and the owner can be notified simultaneously  

scholarly journals To detect abnormal event at ATM system by using image processing based on IOT technologies

2018 ◽  
Vol 7 (3) ◽  
pp. 1000 ◽  
Author(s):  
Kande Archana ◽  
P Bhaskara Reddy
Keyword(s):  
Embedded System ◽  
Dc Motor ◽  
Vibration Sensor ◽  
Stepper Motor ◽  
Time Data ◽  
Police Station ◽  
High Security ◽  
Lcd Display ◽  
Door Lock ◽  
Lcd Displays

Now a day’s ATMs are equipped with money there is possibility of robberies. This paper proposes a framework which will provide high security in ATMs. The Prototype includes ARM controller, Vibration Sensor, GSM and GPS Technique, DC Motor, Stepper motor, Buzz-er, LCD Display, and Keil Tool. Whenever robbery occurs, Vibration sensor is used here which senses vibration produced from ATM machine. This system uses ARM controller based embedded system to process real time data collected using the vibration sensor. Once the vibration is sensed the beep sound will occur from the buzzer. DC Motor is used for closing the door of ATM.Stepper motor is used to leak the gas inside the ATM to bring the thief into unconscious stage. Camera is always in processing and sending video continuous to the PC and it will be saved in computer. RTC used to capture the robber occur time and sends the SMS and MMS to the nearby police station and corresponding bank through the GSM and GPS. Here LCD displays board using showing the output of the message continuously. This will prevent the robbery and the person involving in robbery can be easily caught. Here, Keil tools are used to implement the idea and results are obtained. keil tools is used for run the DC motor and stepper motor for automatic door lock and also leak the gas inside the ATM. By this system robberies will be stopped and the complaints cases also reduced maximally. Thus the proposed framework results are revealed that the framework can be providing high security to the ATM System's 

scholarly journals Accident Blackbox Detection using IoT

2020 ◽  
Vol 9 (7) ◽  
pp. 396-399
Keyword(s):  
Mobile Communication ◽  
Human Life ◽  
Black Box ◽  
Vibration Sensor ◽  
Medical Assistance ◽  
Hypothetical Situation ◽  
Police Station ◽  
Contact Person ◽  
Alert Message ◽  
Alcohol Sensor

The accident now happens a few days by car or bike riders, or traffic hazards or any family situation. Accidents resulting from careless driving are increased. When the accident occurs, many people lose their lives because the medical assistance is delayed. Using this black box system this system is designed to detect the basic reason for the accident. Incorporated with GSM, GPS, and sensors. Alcohol sensor detects alcohol and Eye-Blinking sensor conception for sleep while driving the car and using vibration sensor to detect car vibration. Speed is also an important reason why an accident occurred. Using Global Position System knows where the car occurs and uses Global System for Mobile Communication to send alert messages to one of the contact person and nearby hospital and police station. Both GPS and GSM are built into this system. This is connected to the WI-FI network, because GPS will send the location if the accident occurs and GSM will send the message to the contact person and nearby hospital and police station. This system is easy to install under the car because alert message will be sent by the system if an accident occurs. The data for how the accident will occur will be stored in the data base. The base of data is used to justify the accident. For the hypothetical situation this system is used. The system will save human life and decrease the delay of medical assistance.

Detection and Monitoring System for Custody Room Using SW-420 Vibration Sensor with LAN Communication

2019 ◽  
Vol 9 (4) ◽  
pp. 19-24
Author(s):  
Handy Trias Permana
Keyword(s):  
Sensor Node ◽  
Vibration Sensor ◽  
Video Capture ◽  
Detention Center ◽  
Police Station ◽  
Vibration Data ◽  
Vibration Detection ◽  
Manual Methods ◽  
Arduino Uno

Securing detention rooms in Indonesia, using manual methods from humans to secure them. Officers check the detention room periodically. Several cases that occurred, such as the escape of prisoners from the Cawang Police and the Lhoksukhon Detention Center, the detainees broke into the bathroom wall using metal bars to be used as a media for breaking the walls. To prevent recurrence of cases, an early detection design is needed when there is a detention room indicated that it will be damaged by installing a vibration detection device on the wall. In this study, the SW-420 vibration sensor is used as a vibration detector when there is a wall to be broken into and several cameras installed in the corridor to visually monitor the occupants of the detention room. Vibration data will be sent to the detention room website via Arduino Uno, while the IpCamera will be connected to the router to display the video capture results on the website. For example, the bathroom plan for the detention room at the Gondanglegi Police Station that has been made, the sensor node is placed at the center point of the bathroom wall at a position of 60 cm which divides it into 2 parts. Arduino Uno will dynamically have IP when connected to the router using a Lan cable. Based on the experiment in the previous chapter, how to adjust the sensor sensitivity can be done by turning the sensitivity adjustment and adjusting the threshold on the website code.

scholarly journals Real Time ‘Driver Drowsiness’ & Monitoring & Detection Techniques

2020 ◽  
Vol 9 (8) ◽  
pp. 280-284
Keyword(s):  
Real Time ◽  
Transportation Safety ◽  
Small Scale ◽  
Open Area ◽  
Detection Techniques ◽  
Eye Blink ◽  
Driver Drowsiness ◽  
Day By Day

World has seen many of the accidents occur due to driver’s fatigue and a small scale distraction factor while driving the vehicle. Number of accidents has been increasing day-by-day during driving due to driver drowsiness playing as an implicating factor in many accidents. Goal of this thesis is to reduce these accidents and maintenance of transportation safety. The system are design such that it will precisely scrutiny the eye blink. Dissimilarity covering the eye will differ as per eye blink. If outturn is high the eye is closed or else out-turn is low. It shows close or open area of the eye.

scholarly journals IR Remote Control and Eye Blink Sensor based Implementation of Driver Drowsiness Detection

2020 ◽  
Vol 9 (3) ◽  
pp. 3995-3997
Keyword(s):  
Remote Control ◽  
Road Safety ◽  
Eye Blink ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
Everyday Lives ◽  
The World ◽  
Alerting System ◽  
The Usa ◽  
Arduino Microcontroller

Street mishaps are a typical marvel in our everyday lives. Every year these street mishaps prompted numerous passings, deadly wounds and monetary misfortunes everywhere throughout the world. India positions first in the number of street mishap passings over the 199 nations announced in the World Road Statistics, 2018 followed by China and the USA. According to the WHO Global Report on Road Safety 2018, India represents practically 11% of the mishap related passings in the World. One of the major reasons for these mishaps is the sleepiness of drivers. Accordingly, it is important to build up a strategy to recognize the driver's laziness to decrease the mishap rates. In this paper, we have proposed a recognizing, avoidance and alerting system to minimize the street mishaps which are causing due to the sleepiness of drivers using Arduino Microcontroller, Eye Blink Sensor, IR Remote Control and IR Remote Receive Module.

scholarly journals P133 Backward Rotating Shifts are Associated with Real-Time Drowsiness During Daytime Drives in Heavy Vehicle Drivers

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A64-A65
Author(s):  
S Shekari Soleimanloo ◽  
T Sletten ◽  
A Clark ◽  
J Cori ◽  
A Wolkow ◽  
...  
Keyword(s):  
Real Time ◽  
Regression Models ◽  
Heavy Vehicle ◽  
Linear Regression Models ◽  
Daytime Drowsiness ◽  
Eye Blink ◽  
Driver Drowsiness ◽  
Event Rates ◽  
Work Scheduling ◽  
Night Shifts

Abstract Purpose While 10–20% of heavy vehicle crashes (HVDs) are drowsiness-related, the contributions of subsequent shifts to chronic drowsiness in HVDs is largely unknown. Eye-blink parameters indicate driver drowsiness reliably. This study examined the association of consecutive shifts and real-time drowsiness in HVDs. Methods Habitual sleep-wake of HVDs (all males, aged 49.5 ± 8 years) was monitored objectively (Philips Actiwatch, N=15) for 5 weeks (5.75± 1.4 hours). Johns Drowsiness Score (JDS, a composite eye-blink parameter in one-min intervals) was monitored for 4 weeks in HVDs (N=14) using an infrared oculography (Optalert, Melbourne, Australia) device. We assessed the association of drowsiness events (JDS equal or larger than 2.6) with consecutive shift types via mixed linear regression models. Results Eigth consecutive shifts increased drowsiness by 1.06 times compared to 2 shifts (8.37 events/h vs 6.77 events/h, P= 0.03). Consecutive shift sequences included afternoons (9%), mornings (29%), nights (5%), mixed rotating shifts (28%), forward-rotating shifts (11%) and backward-rotating shifts (12%). Drowsiness event rates were 1.23 times greater during night consecutive shifts relative to afternoon shifts (8.37 events/h vs 6.67 events/h, P= 0.03). Backward-rotating shifts (morning-night-evening- afternoon) elevated daytime drowsiness between 10 am and 3 pm by 1.55 times (10.01 events/h vs 6.47 events/h, P= 0.016). Conclusions Regardless of the number of consecutive shifts, sequential night shifts increase real-time drowsiness in HVDs, with backward rotating shifts resulting in higher rates of drowsiness events during daytime. The interaction of schedule features should inform the work scheduling of HVDs to reduce the risk of drowsiness.

Camera-Based Eye Blink Detection Algorithm for Assessing Driver Drowsiness

2019 ◽  
Author(s):  
Mohamed Hedi Baccour ◽  
Frauke Driewer ◽  
Enkelejda Kasneci ◽  
Wolfgang Rosenstiel
Keyword(s):  
Detection Algorithm ◽  
Eye Blink ◽  
Driver Drowsiness ◽  
Blink Detection

Driver Drowsiness Detection System Using Sensors

2017 ◽  
Vol 6 (3) ◽  
pp. 139
Author(s):  
Kusuma Kumari B.M ◽  
Sampada Sethi ◽  
Ramakanth Kumar P ◽  
Nishant Kumar ◽  
Atulit Shankar
Keyword(s):  
Detection System ◽  
Low Cost ◽  
Steering Wheel ◽  
Hand Position ◽  
Major Drawback ◽  
Distributed Sensors ◽  
Eye Blink ◽  
Active Safety Systems ◽  
Safety Systems ◽  
Lcd Displays

<p>A low-cost and simple distributed sensors model that is particularly suitable for measuring eye blink of the driver, accident and hand position on a steering wheel. These sensors can be used in automotive active safety systems that aim at detecting driver’s fatigue, a major issue to prevent road accidents. The key point of this approach is to design a prototype of sensor units, so that it can serve as platform for integrating different kinds of sensors into the steering wheel. Since the sensors are attached to the steering wheel, therefore they can’t be detached by the driver. It will also detect dangerous stylish driving which may lead to fatal accidents. The major drawback is that the eye blink sensors frame worn by the driver can be removed causing the sensor non-operational. The outcome is that the vibrator attached to eye blink sensor’s frame vibrates if the driver shuts his eyes for approximately 3 seconds and also the LCD displays the respective warning message. The wheel is slowed or stopped depending on the condition. This is accompanied by the vehicle’s owner being notified through the GSM module, so the owner can retrieve the driver’s location, photograph and a list of nearby police stations through an android mobile application. Therefore, driver can be alerted during drowsiness and the owner can be notified simultaneously.</p>

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