A Real Time Embedded System Application for Driver Drowsiness and Alcoholic Intoxication Detection

Sarkar, Dwipjoy; Chowdhury, Arijit

doi:10.14445/22315381/ijett-v10p288

Cited by 25 publications

(10 citation statements)

References 8 publications

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“…F. In iterative spatiospectral patterns learning (ISSPL), to achieve efficient performance the spectral filters and classifier are simultaneously parameterized for an extension. In ISSPL, a rigorous derivation and theoretical analysis are complicated [9]. G. The implementation of non-invasive type of Brain-Computer Interface technique to control the home appliances using EEG based brain signals.…”

Section: IImentioning

confidence: 99%

A Review on Brain Wave Signal Appliance Control

Beigh¹

2018

IJRASET

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Brain Computer Interface systems are the tools that have been put forward to help the disabled people who are inadequate of retorting to a computer using brain signal. The development in home automation is moving forward towards the future in creating the ideal smart homes environment. Optionally, home automation system design also been develop for certain situation which for those who need a special attention such as old age person, sick patients, and handicapped person. A braincomputer interface (BCI), often called a mind-machine interface (MMI), or sometimes called a brain-machine interface (BMI), it is a direct communication pathway between the brain and an external device. Most research investigating BCI in humans has used scalp-recorded electroencephalography or intracranial electrocorticography. The use of brain signals obtained directly from stereotactic depth electrodes to control a BCI has not previously been explored. In this paper, we present a smart home automation system using brain-computer interface. BCI is becoming progressively studied as the way users interact with computers because recent technological developments have led to low priced, high exactness BCI devices. These systems that can detour conventional channels of communication (i.e., muscles and thoughts) between human brain and corporeal devices, to provide undeviating communication and sway, by recasting different patterns of brain activity into commands in real time. The device tested in this paper is called Neurosky Necomimmi Brainwave Cat Ears, which is an electroencephalograph (EEG) measuring device and enables the measuring of brain bustle. With the help of this, we are analyzing the brain wave signals. Human brain has millions of interconnected neurons. The interaction pattern between these neurons is represented as emotional states and thoughts. This pattern will be changing as the human thoughts change, which in turn produces different electrical waves. These electrical waves will be sensed by the brain wave sensor and it will convert the data into packets and transmit via Bluetooth medium. Keywords: Brain Computer Interface (BCI), Neurons, Brainwave sensor, Electroencephalogram (EEG), Neurosky, and Arduino. I.INTRODUCTION BCI is used to communicate based on human brains neural activity and it is very much independent of output generated by peripheral nerves and muscles. Typical BCI equipment that utilizes EEG to measure brain activity is expensive and requires expert knowledge to setup and use. The signals generated by brain are received by the brain sensor and are divided into packets and the packet data is transmitted to wireless medium (Bluetooth). The wave measuring unit will receive the brain wave in raw data format and it will convert it into signal. Brain-computer interface is nothing but the interaction between the human brain system and machines. It is a control system which enables the people to communicate and control a device by mere thinking. BCI collects the information from the brain and give command...

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Section: IImentioning

confidence: 99%

A Review on Brain Wave Signal Appliance Control

Beigh¹

2018

IJRASET

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“…The samples were liquefied and decontaminated with 4 % NaOH according to the modified Petroff’s method [13]. The decontaminated specimens were inoculated onto Löwenstein–Jensen media (L-J media), LJ media containing Thiophene – 2 carboxylic acid hydrazide (TCH) and p-nitrobenzioc acid (PNB) and cultures were observed for 8 to 12 weeks incubating at 37 °C and at 28 °C in light and dark conditions.…”

Section: Laboratory Analysismentioning

confidence: 99%

Real time PCR for the rapid identification and drug susceptibility of Mycobacteria present in Bronchial washings

et al. 2016

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BackgroundMycobacteria have a spectrum of virulence and different susceptibilities to antibiotics. Distinguishing mycobacterial species is vital as patients with non-tuberculous mycobacterial (NTM) infections present clinical features that are similar to those of patients with tuberculosis. Thus, rapid differentiation of Mycobacterium tuberculosis complex from NTM is critical to administer appropriate treatment. Hence the aim of the study was to rapid identification of mycobacterial species present in bronchial washings using multiplex real time Polymerase Chain Reaction (PCR) and to determine the drug susceptibility in identified mycobacterial species.MethodsSputum smear negative bronchoscopy specimens (n = 150) were collected for a period of one year, from patients attending the General Hospital Kandy, Sri Lanka. The specimens were processed with modified Petroff’s method and were cultured on Löwenstein– Jensen medium. DNA, extracted from the mycobacterial isolates were subjected to a SYBR green mediated real time multiplex, PCR assay with primers specific for the M. tuberculosis complex, M. avium complex, M. chelonae-M.abscessus group and M. fortuitum group. DNA sequencing was performed for the species confirmation, by targeting the 16S rRNA gene and the drug susceptibility testing was performed for the molecularly identified isolates of M. tuberculosis and NTM.ResultsThe optimized SYBR Green mediated multiplex real-time PCR assay was able to identify the presence of genus Mycobacterium in 25 out of 26 AFB positive isolates, two M. tuberculosis complex, three M. avium complex and two isolates belonging to M. chelonae-M. abscessus group. DNA sequencing confirmed the presence of M. tuberculosis, M. chelonae-M. abscessus, M. intracellulare, M. avium, Rhodococcus sp. and M. celatum. Remaining isolates were identified as Mycobacterium sp. All the NTM isolates were sensitive to amikacin and seven were resistant to ciproflaxacin. Twenty two of the NTM isolates and the isolate Rhodococcus was resistant to clarithromycin. The two isolates of M. tuberculosis were sensitive to all first line anti tuberculosis drugs.ConclusionThe optimized SYBR Green mediated multiplex real time PCR assay could be an effective tool for the rapid differentiation of pathogenic M. tuberculosis complex from the opportunistic nontuberculous mycobacteria and also it confirmed the presence of NTM in 15.3 % of the study population.

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“…Some of the system includes a video camera either externally attached or inbuilt camera in Laptop [5].And also the system is used for security purpose [6] Vehicle Theft is prevented by making use of Transmitter-Receiver module [7]. In some of the system, region prop with EDAMAS techniques are used [8].It also combines the application of computer vision with embedded systems and are targeted for reducing road accidents due to driver drowsiness and alcoholic intoxication [9] III SYSTEM DESIGN The block diagram of system is shown in the Fig 1. The system consists of MEMS sensor that is an Accelerometer, Alcohol sensor, Driver circuit, Relays, LCD display, Power supply, PIC Microcontroller, Brake failure detector. Alarm is used in a system to indicate regarding an emergency situation occurred.…”

Section: Literature Surveymentioning

confidence: 99%

Design and Development of Accident Prevention and Control System

Shettar¹,

Dabhade²,

Viraktamath³

et al. 2015

IJERT

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In this paper, three basic circuits for prevention of accident and control measures are been explained. One is accelerometer circuit which is used for detection of drowsiness and second is alcohol sensor circuit which is used for detection and control of a vehicle due to alcohol consumption. Accident due to drowsiness can be prevented using alert mechanism which is controlled by relay when tilt motion is detected and it is sensed by single step accelerometer. Similarly relay turnoff the ignition process of a vehicle if level of the alcohol is sensed above the normal by a sensor. Along with this brake failure detection is also done by checking the continuity if not the vehicle owner is made alert to prevent the accidents from brake failure.

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A Real Time Embedded System Application for Driver Drowsiness and Alcoholic Intoxication Detection

Cited by 25 publications

References 8 publications

A Review on Brain Wave Signal Appliance Control

A Review on Brain Wave Signal Appliance Control

Real time PCR for the rapid identification and drug susceptibility of Mycobacteria present in Bronchial washings

Design and Development of Accident Prevention and Control System

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