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Development of smart bike with integrated navigation system to detect live traffic and implementing voice interrogation using smart sense technology.


This project is split into 6 different sections according to the fixing of the microcontrollers. Bike, Helmet, Gps And Mobile Application, Charging System, Communication System.

1.1 Bike:

This bike is operated by eight 12v lead acid batteries which are divided into two parts one as primary and another four as secondary. The bike has an integrated licence checking system and voice interrogation enabling the rides to directly interrogate with the bike. It also has an inbuilt navigation system which can show live traffic conditions.

The license checking system has a RFID sensor which scans for the licence once the licence is placed on it by the rider. Every valid licence cards are actually RFID tags whose IDs are already stored in the RTO cloud. These ID stored in the RTO cloud can only be edited or any addition of new ID tags be done by the RTO only. The microcontroller in bike can only read the TAG ID from the RTO cloud. Once the placed license matches with the TAG ID in the cloud one of the relay in the relay module is turned ON and the MCU asks for the key. The rider has to turn the key ON which intern turns the second relay ON. Now the MCU reads the information provided by the helmet, once all the conditions are satisfied the last relay is turned ON and the bike IGNITION system is turned ON enabling the rider to ride the bike. All the above process is instantly reported in a LCD display attached with the bike and also displayed in the MOBILE APP.

1.1.1 Block Diagram Of Bike:

1.2 Helmet:

The helmet is integrated with MQ-3 sensor and earlobe sensor. The earlobe sensor checks whether the rider has worn the helmet properly by checking the shape of the earlobe and heartbeat so that helmet check cannot override in any means. The Earlobe sensor is connected to a MCU unit which checks whether the amount of alcohol consumed by the rider is allowed. Once the Helmet wear check is completed successfully the MCU turns ON one of the relay attached to the helmet. If the helmet wear check has failed, the MCU sends a signal to the bike unit to display that the helmet is not worn properly. The helmet also checks whether the rider has consumed alcohol by using MQ-3 sensor. The MQ-3 sensor checks whether the rider has consumed alcohol more than the allowed value, the values are processed by the MCU and once the value exceeds the allowed value a signal is sent to the BIKE unit to display that the rider has consumed alcohol. Once the two conditions satisfy, a signal is send to the MCU to turn the second ignition relay ON

1.2.1 Block Diagram Of Helmet:


An advanced automated GPS navigation system is attached to the BIKE UNIT. The navigation system is connected to GOOGLE MAPS and can be used to search for any place all over the globe. this navigation system is turned on by launching a mobile app. This uses triangulation method to track the location of the bike and also works without internet connection. The rider has to set or search for their destination either manually or by voice command i.e., (saying "let's go home" will trigger the navigation system with destination to the rider's home)

The rider can still select for route which has NO TOLL BOOTH, NO FERRIES, NO HIGHWAYS manually.


The integrated GPS technology can also alert you any traffic change in any instant automatically and also calculates the time the rider has to spend to cross that traffic.

If there is any change in the traffic condition while navigating like any congestion in road, the app will also report it to the rider.

SENSE also holds a cloud database of all blocked routes and roads which are under construction. If the rider selects a route where the roads are blocked or the road which is under construction. The app will let them know.

SENSE also divides the destination into separate modules and adds pit stops in-between if the destination is too long.

SENSE can also inform whether the destination is open or closed at the time they arrive the destination. All this information is automated and the riders do not need to worry about anything.

This app can also be used to track your bike if your bike is lost. All areas are also available off-line and can be downloaded by the users to use navigation offline. Traffic data are displayed only when you are online.

1.4 Charging System:

The bike runs with eight 12v batteries are divided into two parts, the first four batteries are primary and the second four batteries are secondary batteries. The bike initially runs on the primary batteries and a dynamo attached to the front wheel of the bike charges the secondary batteries. Once the primary batteries are fully drained and at the same time the secondary batteries would have charged. The automated charging system switches the source to secondary. Now the bike will run in secondary batteries and the primary batteries gets charged and this cycle is repeated. The loss in energy in the form of HEAT and MAGNETIC FLUX is overcome by a solar panel attached to the charging system thus the energy is recycled to its fullest.

The charging technology used here is knows as DASH CHARGE, the same technology used in one plus 3T devices for a safer and faster charge. The DASH CHARGE charges the BIKE in 2 hrs and you are good to go for the next 250 KM where other battery operated bikes run only for 70-80 KM.

1.4.1 Block Diagram Of Charging System

1.5 The Communication System:

All communication between the helmet - bike, bike-GPS, and charging system are all wireless. The helmet consists of a RF transmitter which transmits the data manipulated in it to the BIKE i.e., (Alcohol value, Relay state). The bike has a RF receiver which receives the data from the helmet.

Bike also communicates with the mobile app by using HC-05 Bluetooth module. The bike sends all data like helmet check results, bike location, ignition state, relay state to the mobile app. it also receives voice commands given to the mobile.

II. Mcu Unit:

The charging unit is controlled by Arduino Nano microcontroller. The bike unit has a integrated Arduino Mega ATmega 2560 microcontroller to manipulate, process and automate all bike functions including the charging system. The helmet uses a Arduino Nano microcontroller unit to process the data .
Key parameters for ATmega2560


Flash (Kbytes):               -- 256 Kbytes
Pin Count:                    -- 100
Max. Operating Freq. (MHz):   16 MHz
CPU:                          -- 8-bit AVR
Max I/O Pins:                 -- 86
Ext Interrupts:               -- 32
SPI:                          -- 5
ADC Channels:                 -- 16
ADC Resolution (bits):        -- 10
ADC Speed (ksps):             -- 15
Analog Comparators:           -- 1
SRAM (Kbytes):                -- 8
EEPROM (Bytes):               -- 4096
I/O Supply Class:             -- 1.8 to 5.5
Operating Voltage (Vcc):      -- 1.8 to 5.5
Timers:                       -- 6
Output Compare Channels:      -- 16
Input Capture Channels:       -- 4
PWM Channels:                 -- 15


[1.] CDC, U.S., "Traffic Detection Application", http://www.cdc.govTrafficDetectionlimpaired-drvjactsheet.html


[3.] Weiland, R. and L. Purser, 2009. "Intelligent Transportation Systems," Transportation Research, 1: 40AM.

[4.] Knaian, A., 2000. "A wireless sensor network for smart roadbeds and intelligent transportation systems,"

[5.] Ph.D. dissertation, Citeseer.

[6.] National Highway Traffic Administration. Fatality Analysis Reporting System (FARS). 2009 [cited 2009 June]; Available from :

[7.] Smart Helmet with Sensors for Accident Prevention Mohd Khairul Afiq Mohd Rasli, Nina Korlina Madzhi, Juliana Johari Faculty of Electrical Engineering University Tecnology MARA40450 Shah Alam Selangor,

[8.] Smart, A. Safety Helmet using IMU and EEG sensors for worker fatigue detection Ping Li, Ramy Meziane, Martin J.-D. Otis, Hassan Ezzaidi, REPARTI Center, University of Quebec at Chicoutimi Chicoutimi, Canada Email: Philippe Cardou REPARTI Center, Laval University Quebec, Canada

[9.] Road accidents in India [online] 2007 June 25. Available from: URL: road-experience/road-accidents-inindia-834.html

[10.] Articles base directory [online] 2011 Feb. 16 Available from: URL:,,5519345,00.html

[11.] The 8051 Microcontroller and Embedded Systems using assembly and C, Muhammad Ali Mazidi & Janice Gillispie Mazidi

[12.] "Vehicle accident alert and locator" International Journal of Electrical & Computer Sciences IJECS-IJENS 11: 02.

(1) J. Josephine and (2) N. Abiram

(1) Assistant Professor, Gkm College Of Engineering And Technology, Chennai.

(2) Ug Student, Gkm College Of Engineering And Technology, Chennai

Received 28 January 2017; Accepted 22 April 2017; Available online 1 May 2017

Address For Correspondence:

J. Josephine, Assistant Professor, Gkm College Of Engineering And Technology, Chennai.


Caption: Fig. 1.1.1: (RFID reader)

Caption: Fig. 1.1.2:

Caption: Fig. 1.2: (Helmet)

Caption: Fig. 1.3.1: (Route selection)

Caption: Fig. 1.3.2: (Route option)

Caption: Fig. 1.3.3: (Live traffic notification)

Caption: Fig. 1.3.4: (Congestion notification)

Caption: Fig. 1.3.5: (Road blocked)

Caption: Fig. 1.3.6: (Pit stop)

Caption: Fig. 1.4: (Charging system)

Caption: Fig. 1.4.1: (Mcu Of Charging System)

Caption: Fig. 1.5: (RF transmitter)

Caption: Fig. 1.5.1: (RF receiver)

Caption: Fig. 1.5.2: (HC - 05 Bluetooth module)
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Author:Josephine, J.; Abiram, N.
Publication:Advances in Natural and Applied Sciences
Article Type:Report
Date:Apr 15, 2017
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