IoT BASED SMART HELMET

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 09 Issue: 04 | Apr 2022 www.irjet.net p-ISSN: 2395-0072
© 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 3277
IoT BASED SMART HELMET
Dr. S.Sekar1, L.Jaivenkatesh2, S.Aravind Kumar3, K.Dinesh Kumar4, N.Jeevanantham5
1Assistant Professor (Sel.G), Department of IT, SRM Valliammai Engineering College Chennai, India
2,3,4,5 Student, Department of Information Technology, SRM Valliammai Engineering College Chennai, India
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Abstract - Accidents are increasing day by day, alsothereis
many laws and regulations are posed by government in order
to avoid this road accidents. Accidents can be the unplanned
event or the mistake that may occur resulting in injury and
sometimes it also leads to death. The accidents occur in two
wheelers are more compared to other vehicles. Although
enough road rules and regulations are made by the
government to avoid accidents, but the accident rate is
increasing day by day. This may be avoided by wearing
helmets and riding vehiclescarefully. However wearinghelmet
can reduce the risk of accidents majorly. In this smart helmet
system is providing safety to the rider in a most effective and
technological way using Internet of Things (IoT) has been
implemented for accident prevention, accident detection and
also quick GPS location recovery system. This proposal also
helps to understand IoT technology which is being emerged
now a day’s .From the method proposed using Arduino UNO,
MEGA and other cost effective sensors like an IR sensor. The
bike engine will start only when the riderwillwornthehelmet.
It detects the head of the bike rider within the range. A Radio
Frequency (RF) Module is used for wireless communication
between helmet unit as transmitter and bike unit as receiver.
Ultrasonic senor used to detect nearby approaching vehicle’s
and send voice alerts to rider by speakers, Most important
utility of this method is that fall detection using Vibrator
Sensor and GSM & GPS module system is included so that
emergency medical service can easily track the location of the
incident occurs and also sending SMS message alert to the
emergency number of the rider stored. Smart helmet system
helps to provide accident detection, safety and security to the
two wheeler riders.
Key Words: Prevention, Detection, Recovery, Smarthelmet,
IoT, GSM GPS location, Sensors.
1. INTRODUCTION
India is the one of the densely most populated country. This
exponential raise in the population and due to the recent
pandemic many people did notprefertouse public transport
to go to their work and to travel this increased sales of the
motor cycles rapidly compared to 2019, the sales has been
doubled in 2022 this increase the traffic among the Indian
roads and increase in the number of road accidents
according to the 2019 report 42% of accidentsoccurinIndia
are because of motorcycles. There are several causes for
road accidents in India the major cause for road accidents
are given below.
Over speeding: Most of the accidents are occur due to the
over speeding it is the natural psychologyofhumanstoexcel
and to win, if there is a chance human will go to infinity in
speed. But as the speed thrills it also kills, faster vehicles
riders are more prone to accident.
Drunken Driving: Consumption of alcohol to celebrate any
instance is very common. But when itismixedwithdrivingit
turns enjoyment to misery. Alcohol can reduces
concentration of riding. It decreases reaction time of a rider
body. Hands and legs take more time to react. It suppress
vision due to dizziness. Alcohol dampens fear and incite
humans to take risks. All these factors while driving cause
accident.
Avoiding safety gears and helmet: Most of the motor cycle
riders doesn’t wear helmet while driving the motor cycle
many studies have shown that helmets and other safety
gears reduce the impact of the accident to a great extend but
many did not wear even though it is made into law.
1.1 Statement of Problem
In the time of study for the project we considered various
scenarios the accidents in case of two wheelers are more
compared to other vehicles. Although enoughroadrules and
regulations are made by the government to avoid accidents,
but the accident rate is increasing day by day when
occurring at remote places are becoming fatal due to the
slow reach of treatment sometimes the person only gets the
medical assistance after 6 to 7 hours this increasesthedeath
rate on an accident and it is evident that when an accident
occurred in the city, they got medical help or assistance
within 30 minutes. Riding withoutproperhelmet equipment
and consumption of alcohol mostly ends with road accident.
Also not following government road rules and regulation,
reckless driving can also cause accident. These can be
reduced or solved by using the Smart helmet system which
helps to provide accident detection, safety and security to
the bike riders.
1.2 Aim and Objectives of the project:
The main objectives of the project are:
 To develop a smart system that provides safety to
motorcycle riders.

 To design a model that reduces the road accidents.
 To design a smart system in which the ignition starts
only when the helmet is worn properly and alcohol is
not detected.
 To design a smart system which recognize and
respond, the vehicles coming from sides of the rider.
 To design a system that alerts the family
members/friends by giving information about the
accidents.
To develop a program for detecting accidentsandsending
an alert message with current location to nearby ambulance
and family member automatically.
2. RELATED WORK
This lecture survey presents previous work related to our
proposed system. Many great contributors had placed a
significant sign in the field of IoT and Knowledge-based
expert systems. We have highlighted some of them to
identify the significant attributes of these systems.
Mohammad Ehsanul Alim et.al [1] has given an approach
Arduino NANOandArduinoMega-2560aremicrocontrollers
which control the entire components of the system. Two 2.4
GHZ nRF24L01 for communication between sender and
receiver. MQ-3 alcohol sensor is used which can detect
whether the bike rider is consumed alcohol ornot.Ifthebike
rider is alcoholic, then the MQ3 sensor detects it and turn off
engine. A Sharp IR sensor detects the head of the rider
within the specified range. The Bike rider’s engine will start
only when the rider will buckle the helmet. GPS & GSM
Technology is used for tracking the location of the bike rider
and sending text message to the family members of the Bike
rider when an accident occurs.
Dhruvesh H. Patelhas et.al [2] proposed an approach which
the System is plan and implemented such a waythatthebike
will not ignite until the rider wear helmet and pass an
alcohol test, this will help to solve the problem of 'drink and
drive'. It consists of GSM GPS technology which sends the
message to the family member as well as hospital with the
current location at the time of an accident.
Saima Siddique Tashfia et.al [3] has proposed scheme
reflects on the embodiment of a smart helmet, having an
alcohol detection sensor to diagnose if the rider wears a
helmet or is drunk. The expert system processes the
information about bike speed, engine temperature, distance
with the nearby vehicle, and location tracking. In the case of
an accident, the system immediatelysendsanSMS,including
GPS location to the emergency contacts. The proposed
Expert System which analyzes IoT cloud data and gives a
possible solution to identified problems.
Sandhya.A.Kulkarni et.al [4] has proposed the smart helmet
system is equipped with advanced alcohol sensing, potholes,
speed breakers and fall detection modules. The bikes
ignition will be avoided, if the rider has consumed alcohol
the system not letting the rider to ride bike. The proposed
system is detecting alcohol concentration from 0.05 mg/l to
10 mg/l by using MQ-3 alcohol sensor, able to identify
potholes and humps within range of 2cm-400cm. Global
System for Mobile Communication and Global Positioning
System are used to send the information to the registered
number, if the biker meets with accident.
Pranav Pathak et.al [5] has proposed a smart helmet system
has two units, the helmet unit (HU) and a motorbike unit
(MU). Both the parts linked radiofrequency(RF).Thehelmet
has the sensors to detect the pulse of the human, the alcohol
content in breath of the rider, and the intensity of vibration.
The pulse sensor is used to detect helmet worn or not. The
GPS and GSM module are used to share location and to send
message. Accelerometer used for detecting accident. The
sensor on bike helps to ensure that the rider is in perfect
riding position, if accident detected send message to
emergency contact. A LIDAR sensor used to detect vehicles
approaching behind. Force-sensitive resistors are used to
detect perfect riding position.
Keesari Shravya [6] has proposed a system to identify
whether the rider worn the helmet or not. If the rider worn
the helmet then ignition will start the engine otherwise it
remains off. For this, Force Sensing Sensor sensor is used.
The second step is alcohol detection [2]. Alcohol sensor is
used to detect the presence of alcohol in rider’s breath and if
it detects ignition cannot start.
Navya Sri K [7] proposed a system with GPS and GSM for
accident detection. It uses push button to detect an accident
and if the accident occurs location will be sent to the contact
list saved in EEPROM.
H.C. Impana [8] has given a method method proposed using
microcontroller RF transmitter and other sensors is cost
effective but we find the system proposed using Raspberry
pi module, Pi camera, Pressure Sensor, GPS system which
uses image processing algorithms is most useful since the
image processing is included so that we can easily detectthe
helmet from the rider.
Souhardya Das et.al [9] the smart helmet is providing safety
to the rider. This is developed using the method of alcohol
detection, accident detection, get real time location, and fall
detection .The rider should wear safety equipment
otherwise engine will not start. An RF Module is used as a
communication link betweenhelmetunitandbikeunit.If the
rider is drunk the ignition gets automatically locked, and
sends information to a contact number with the current
location.

3. PROPOSED SYSTEM
The first issue concentrates to prevent not wearing helmet
and detect the rider is drunken drive these factors are the
main reason for the accident cause. If the helmet is not worn
properly the ignition of the bike is blocked and will not start
and when the helmet is worn by the rider it will also check
for alcohol condition if the rider consumed any alcohol, it
will detect and the ignition will automatically stop for this
module IR sensor and MQ-3 sensors are used. The IR sensor
is fitted inside the helmet so it can detect theriderhead.This
eliminates the case of the rider keep the helmet on the top of
bike fuel tank. The MQ-3 gas sensor is fitted in front of the
rider mouth of the helmet. It detects the alcohol and set the
value to HIGH means the alcohol is detected and bike
ignition will stop. A Radio Frequency (RF)Moduleisused for
wireless communication betweenhelmetunitastransmitter
and bike unit as receiver. The second issue is while riding a
motorcycle there are many blind spots so the rider doesn’t
know whether a vehicle is approaching or not this cause
major accident to the riders who follow the rules to
overcome this issue ultrasonic sensors are placed in the all
three side (Left, Right, Back) to intimate about the vehicles
approaching the rider using the voice module and speakers.
The final issue is when a rider met with an accident it takes
more time to get medical help and rider’s friend and family
doesn’t know about what has happened to him, to overcome
this issue GSM and GPS modules are used to detect the
location where the accidents occur and send the location to
the emergency contacts saved inside thedeviceFig-1.Shows
the overall architecture overview of our proposed system.
Fig-1: System Architecture of complete system
The system is consist of two units are Bike Unit and Helmet
Unit in which the helmet unit contains Arduino UNO , IR
sensor for detection of rider head, MQ-3 sensor for alcohol
detection, and NRF24L01 transmitter and receiver to
establish wireless communication between helmet unit and
bike unit. Fig-2. Represent the flow diagram of the Helmet
unit implemented.
Fig-2: Flow chart for the Helmet Unit
In Helmet unit the system initialize all ports and establish
connection between RF (Radio Frequency) transmitters to
receiver. The system checks the condition whether the
helmet is worn properly and check consumption of alcohol.
If the above condition satisfy thentheRFsendssignal toBike
unit to start the ignition otherwise the engine won’t start it
shows alert in LCD display.
Fig-3: Flow diagram for the Bike Unit
In Bike unit is consist of Arduino MEGA,Ultrasonic Sensor
(HC-SR04) for surrounding vehicle detection,GSM SIM800L
modules are used to send notification alert SMS and to

emergency contacts. GPS Neo 6m fetch the accident location
transferred to SIM800L. Accelerometer Sensor, Vibrator
Sensor are used to detect the axis change and vibration
during accident Fig-3. Represent the flow diagram of the
Bike unit. When the RF get the signal from the helmet unit
the bike engine start and even the bike start it continuously
detecting the helmet unit. The system detects the nearby
vehicle if only the rider reach the over speed above40kmph,
the ultrasonic sensors detects the vehiclewithintherange of
30cm from the three sides. If the vehicle approach the rider
left side, the system sends the voice alert to helmet unit via
bluetooth speakers are placed inside the helmet. i.e.“Vehicle
on Left”. Then there is any sudden changes in axis readings
of the bike it check the vibration value. If the accident occurs
GPS location coordinates fetched and stored in GSM module
it send the immediate SMS to emergency ambulance and as
well as family members. So this system reduce the time
taken to reach the accident location and they got medical
help or assistance soon.
4. METHODOLOGY
The methodology of the proposed IoT based Smart Helmet
system contains two interconnected units that is separated
using wireless communication between the Helmet Unit
(Arduino UNO) act as transmitterandtheBikeUnit(Arduino
MEGA) act as receiver. NRF24L01 Transmitter & Receiver
Module is used to establish these two wireless connection.
Smart helmet system is planned and implemented in such a
way that the two-wheeler will not ignite until the rider wear
worn the helmet properly using IR sensor and pass an
alcohol test by MQ-3 sensor which will help to solve the
problem of drink and drive. To prevent accident by alerting
the rider of nearby vehicles coming using Ultrasonic Sensor.
Detecting the accident and tracking the location of the
accident using GPS neo6m and sends SMS to emergency
contact by GSM800L.This systemcontainsthreemodules are
explained below Helmet detection – Accident Prevention,
Vehicle detection and Accident and fall detection.
4.1 Helmet detection - Accident Prevention
To check whether the rider wear the helmet properly ornot.
By the IR – Infrared Sensor placed inside the helmet in
position located in-front of the rider head it confirms the
helmet worn properly. It eliminates the rider to keep the
helmet on the top of fuel tank of the bike. This sensordetects
the head of the rider between 5 cm and 30 cm away. IR
sensor sends the signal to check whether rider consumed
alcohol or not by MQ-3 Gas sensor. The gas sensor
continuously checking the alcohol values, the condition in
checked the alcohol value by varying in values. Alcohol gas
value is different from normal gas. If the rider worn the
helmet properly but consumed alcohol means its lock the
engine ignition. Both the condition needs to satisfy in order
to ignite the bike engine. When the bike ignition lock is
opened the RF receiver will wait for the signal from the
helmet unit. When the rider wears the helmet and not
consumed alcohol the transmitter will send the signal to the
receiver so that bike can be started. If the bike rider doesn’t
wear the helmet properly the ignition won’t get start.
Fig-4: IR Sensor
Fig-5: Helmet Unit Structure
4.2 Vehicle detection
For vehicle detection in the bike unit, IR sensor is also used
for measuring the rpm speed of the bike. If rider reach the
over speed above 40Kmph the bike unit starts detecting the
nearby vehicle using 3-Ultrasonic Sensor placed in the three
directions like left, right and back side and it sends voice
alerts to helmet speakers by wireless Bluetooth connection.
The Ultrasonic sensor gives the distance value ofhowfarthe
object is moving. APR33a3 Voice module is used for
recording voice alerts. The system eliminates the chances in
order to the accident occur. The rider will not irritate by
voice alerts when the other vehicle passing them
continuously for example in Traffic jam. The bike unit only
detects the nearly vehicle in the range below < 30cmandthe
system alerts only once at a time.
4.3 Accident and fall detection
The bike unit will detect the crash or accident by using the
ADXL3xx accelerometer sensor and vibrator sensor. If there

is any sudden changes in accelerometer readings then it
verify the vibrator value system will beep continuously and
will shows alert in LCD. If accident occurred then the GPS
neo6m module fetch the location coordinates. The
information and location link will be sent to emergency
contacts stored in memory using GSM SIM800L module. It
sends the SMS to emergency contact as well as a family
member with the current location of an accident.
5. HARDWARE AND SOFTWARE COMPONENTS
USED IN IOT BASED SMART HELMET
The following section is used to describe about the
components used in this system.
5.1 Arduino UNO
Arduino Uno microcontroller is used in helmetunit(HU).It’s
a microcontroller board based ontheATmega328P.Ithas14
digital Input/output pins of which 6 can be used as PWM
outputs, 16 MHz quartz crystal oscillator, six analog inputs,
USB connection, 12V power jack, an ICSPheader. It’ssmall in
size and portable.
5.2 Arduino MEGA
The Arduino Mega 2560 is used in Bike unit. It’s a
microcontroller board based on the ATmega2560. It has 54
digital Input/output pins of 15 can be used as PWM outputs,
16 analog inputs, four UARTs (hardware serial ports), a 16
MHz quartz crystal oscillator, USB connection, 12V power
jack and ICSP header. It contains more digital pinscompared
to UNO.
5.3 MQ-3 Gas sensor
This Alcohol Gas Sensor MQ3 is used to detect alcohol gas.
It is an efficient semiconductor sensor which can detect the
presence of alcohol gases at concentrations from 0.05 mg/L
to 10 mg/L and low cost. The alcohol gas unitismeasuredby
Parts-per-million (ppm).
5.4 APR33a3 Voice module
APR33A3 is a module can record 8 Voice Channel and Audio
playback board integrated with APR33A series IC which is a
significant audio microprocessor along with high-
performance audio converters. It’s used to record voice
alerts of nearby vehicles.
5.5 IR Sensor
An infrared sensor (IR sensor) is used to detect the rider
head and also measure the rpm speed of the bike. It’s a
radiation-sensitiveoptoelectronic componentwitha spectral
sensitivity in the infrared wavelength range 780 nm 50 µm.
IR sensors are now widely used in anti—theft motion
detectors, which are used in building services to switch on
lamps or in alarm systems to detect unwelcome guests.
5.6 NRF24L01 Transmitter & Receiver Module
The nRF24L01 is widely used in the wireless control
applications. This used for the wireless communication
between the helmet unit and bike unit. They are bi-
directional so transceivers which this meansthemodulecan
transmit and receive data. Low power consumption with
long range access.
5.7 Vibrator Sensor
Vibration sensors are piezoelectric accelerometers that
sense vibration. They are used for measuring fluctuating
accelerations or vibration produced during the accident or
for normal vibration measurement. This sensors now used
by maintenance professional’s use the sensors in order to
predict the need of maintenance of the machinery.
5.8 ADXL3xx Accelerometer Sensor
Accelerometer sensors are ICs that measure acceleration in
which is the change in speed (velocity) per unit time.
Measuring acceleration makes it possible to obtain
information about the axis. M/s2 unit for acceleration.
Gravity (G) is also used as a unit for acceleration, relative to
standard gravity (1g = 9.80665m/s2).Otherusageincludeto
measure tilt axis of the bike.
5.9 GSM SIM800L Module
SIM800L is a miniature 2G cellular module which allows for
GPRS transmission, sending and receiving SMS and making
and receiving voice calls. Long range connectivity with low
cost and quad band frequency support make this module
perfect solution for any project. Here it is used to send alert
SMS.
5.10 GPS Neo 6m
The NEO-6M GPS module is used to detect the accident
location which can connect upto 22 satellites. The GPS
module is well-performing complete GPS receiver with a
ceramic antenna, which provides a strong satellite search
capability and accurate location with date, time. Its low
consumption of 3.3v only required.
5.11 Ultrasonic Sensor (HC-SR04)
The HC-SR04 Ultrasonic Distance Sensor is a sensorusedfor
detecting the vehicle to a rider using sonar waves. It
measures using the echo and triggers the distance between
the two objects. These are used todetectthenearbyvehicles.

5.12 Bluetooth Transmitter and Receiver
Bluetooth which can operates in 2.4 GHz wireless
communication channel.Theseareusedtoestablishwireless
audio alerts transfer seamlessly and consumption of power
less and low cost.
6. EXPERIMENT AND RESULT
In this experiment, results of our implemented system as
well as the relevant details. This system can be divided into
four consecutive parts which work together:
A) Detecting the rider status.
B) Detecting the nearby vehicles.
C) Location tracking.
D) Analyzing the accidental situation.
6.1 Detecting the rider status:
The system is proposed detecting whether the rider wears a
helmet or not and sensing consumption of the alcohol level.
The first step of system is it initializes all the port and first
step is to check weather helmet is wear or not.IfHelmetisnot
worn then display alert in LCD Fig-8 will be displayed. Next
step is to check the condition of alcohol, ifriderisdrunk,Fig-6
MQ3 check the reading values and send signals.
The bike unit RF receiver block the engine ignition and stop
the bike.
Fig-6: Helmet Unit Connection
Both two conditions are being checked continuously-
1) Whether the rider worn a helmet or not and
2) Whether the rider is drunk or not.
By using IR sensor for sensing the presence of helmet on
their head and MQ-3 gas sensor detects the alcohol level.
According to the IR and MQ3 reading values in Table-1,
IR sensor is positioned inside the helmet range islesserthan
equal to 20cm in order to detect theriderheadotherwisethe
helmet is not detected. Alcohol detect in clean air is 0.04
mg/L. In our readout analog value must be below 800 after
analyse the normal breath range is from 100 to 800. When
the sensor detected the alcohol it set range value above 800
so the rider is drunk and engine will stop.
Table-1: Reading Values of IR and MQ3 Sensor
SI. IR sensor
(range
<=20cm)
Helmet Alcohol detect
(Drunk >=
800ppm)
Signal
Engine
1. 5 YES 820 OFF
2. 2 YES 500 ON
3. 10 YES 300 ON
4. 15 NO 200 OFF
5. 30 NO 250 OFF
6.2 Detecting nearby vehicle:
To prevent the accidents and at a same time helmet act as an
assistant during the ride. At night rider can’t see the nearby
vehicle approaching them. In thatsituationonevoicealert can
save his life to avoid accident. This unique feature
implemented in Bike unit by using Ultrasonicsensorsinthree
sides of the blind spots.
Fig-7: Bike rider blind spots

Table-2: Readings Value of Ultrasonic Voice Alerts
ULTRASONIC SENSOR VOICE ALERT
SI. LEFT
(range
<=30cm)
RIGHT
(range
<=30cm)
BACK
(range
<=30cm)
Left
Alert
Right
Alert
Back
Alert
1. 25 0 50 YES NO NO
2. 40 10 50 NO YES NO
3. 50 0 30 NO NO YES
4. 15 40 20 YES NO YES
5. 30 15 40 YES YES NO
6. 40 10 20 NO YES YES
7. 10 20 30 YES YES YES
In bike unit, ultrasonic sensor from sides startsdetectingthe
nearby vehicle only when the rider reach the over speed
above 40kmph. Table-2, shows the distance range of the
approaching vehicle is detected by Ultrasonic.
If the vehicle distance lesser than or equal to 30cm the bike
unit sends the voice alerts from ARP33a3 voice module to
Bluetooth transmitter. The receiver in helmet transfers the
voice into speakers inside helmet. I.e. voice alert also LCD
displays “VEHICLE ON LEFT”. The system stop detecting the
nearby vehicle when speed is low in traffic jam situation.
The voice alert occurs only once at per vehicle passed so it
can’t irritate the rider by voice.
Table- 3: Voice Alert Commands
SI. VOICE ALERTS COMMANDS
1. LEFT Vehicle On Left
2. RIGHT Vehicle On Right
3. BACK Vehicle On Back
4. LEFT RIGHT Vehicle On Left Right
5. LEFT BACK Vehicle On Left Back
6. RIGHT BACK Vehicle On Right Back
7. ALL SIDE Vehicle On All side
Fig-8: Display alerts
Table-3. Shows the voice alerts and the sides of the vehicle
approaching the bike rider.
Fig-9: Bike Unit Connections
6.3 Location tracking
The bike unit Fig-9.controls the both vehicle detection and
accident detection. Location tracking using GPS coordinates
neo6m module used for tracking the biker’s real-time
location, GSM SIM800L module is used to send the SMS
location coordinates to the emergencynumberarestored and
ambulance in the hospital. Whenever the bike system detects
an accident, an alert message displays, including real-time
location coordinates with Google Map link, is sent to the
emergency number.Usingthegeographical positionlongitude
and latitude values, the authorized person can find the exact
location of the rider.
6.4 Analyzing the accidental situation:
Analyzing the Accelerometer sensor (ADXL3xx) data for
detecting accidental situation in the bike. Vibration is
common in bikes so it cannot be determined the accident is
occurred so that the bike has two condition need to be true:

1) Whether any changes in position of bike axis
2) Check whether the reading increasing valuesinvibrator
Fig-10: Axis position change in Accelerometer sensor
If there is any sudden changes in bike axis is detected by
Accelerometer sensor to check tilt angle then the vibrator
sensor check the vibrationvalues.Inaccelerometerhasthree
reading values are x-axis, y-axis,andz-axis.Fig-10.Showsthe
representation of bike axis is changed. These sensor detects
the fallen bike by changes in axis position values to detect
accident condition show in Table-4.
Above table shows the bike in stable normal position and
after the accident is occurred. Next step the vibration value
is checked whether the value is above 7000 means strong
vibration. If the both conditions are true then the alert
display and the GPS location is fetched sent to emergency
number stored in GSM module via SMS. AlsoitsendstheSMS
to rider family member.
Table-4: Accident Detection Readings
ACCELEROMETER VIBRATOR SMS
ALERT
SI X-axis
(-250
to
+350)
Y-axis
(-260
to
+330)
Z-axis
(-275
to
+410)
Range
>=7000
1. 329 326 404 4000 NO
2. 340 269 337 7500 YES
3. 266 325 348 8000 YES
4. 328 329 405 5000 NO
If accident occurs and bike falls, then it displays the alert
message on LCD and sends an SMS to the emergency number
with the current google map location link, accident occurred
date will be shown.
7. CONCLUSIONS AND FUTURE ENHANCEMENT
Ultimately, the System is focused on the safety of riders, by
obligatory use of safety equipment. Additionally, it provides
certainty of non-consumption of alcohol throughout ride.
The ignition system prevent rider to start a bike when rider
violate any of security rules. This system overcomes many
condition faced in previous system. The Unique feature in
helmet unit is system act as an assistant when the limit
speed reached by the bike, it start detecting the nearby
vehicles and give voice alert to the rider. Furthermore,
reporting system helps to inform family member for
immediate treatment via SMS with location in case of
accident occurs. Hence the cost is very low. In future we can
improve the vehicle detection model to detect the potholes
and speed brakes in the road. To reduce the sensor
processing time load on the microcontroller by developinga
dedicated embedded system for this purpose. Using
Raspberry Pi with the Pi camera module and adjust its
position in such a way that you could observe the projection
on the mirror of the helmet and Small solar panels can also
be attached on the top and backside of the helmet so thatthe
need for the battery is minimized and the weight of the
circuitry can further be reduced.
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[9] Souhardya Das,SahadebSantra,SanketSinha”Smart
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