Smart Helmet for Safe Ride

DOI : 10.17577/IJERTCONV12IS03100

Download Full-Text PDF Cite this Publication

Text Only Version

Smart Helmet for Safe Ride

Ms.S.Ashika Preethi AP/EEE,

Shree Venkateshwara Hi-Tech Engineering College, Gobichettipalayam, Erode

C.Saravanakumar Department of EEE,

Shree Venkateshwara Hi-Tech Engineering College, Gobichettipalayam, Erode


A smart helmet is a type of protective gear worn by cyclists to improve safety during rides. Its main purpose is to ensure the rider's safety through various features including alcohol detection, accident identification, location tracking, hands- free operation, and fall detection. This makes the helmet not only smart but also integrates it with the bike's ecosystem. Wearing the helmet is mandatory as it's linked to the bike's ignition system. Communication between the helmet and other devices is enabled through an RF module for wireless connectivity. If the rider is found to be intoxicated, the ignition is disabled, and a notification with their location is sent to a designated contact. In case of an accident, a message containing GPS coordinates is sent via GSM for immediate assistance. An additional feature is its capability to detect falls and send automatic notifications.


The impetus behind the initiation of this project stems from a profound sense of social responsibility towards the community's welfare. Globally, numerous accidents occur annually, leading to significant loss of life. A survey conducted in India highlighted a stark reality, revealing that approximately 500 accidents stemming from bike collisions transpire every day. Such statistics underscore the urgent need for initiatives aimed at enhancing safety measures and mitigating the frequency and severity of accidents on the roads. Numerous factors could contribute to the accidents, including reckless driving, insufficient cycling fitness, driving under the influence, etc. In certain instances, the accident may not have been caused by the wounded individual; rather, it may have been caused by another rider. If mishaps are one thing, delayed medical attention is another factor contributing to fatalities. Numerous fatalities result from the failure to wear helmets and delays in receiving timely medical treatment. In remote areas, it's often challenging for emergency services to promptly respond to accidents. By simply wearing a helmet, many lives could be preserved. Approximately 60% of accident-related deaths could be averted with prompt medical attention. This initiative aims to enforce helmet usage among riders and promptly alert emergency services in the event of an accident.

N.Sivanesan Department of EEE,

Shree Venkateshwara Hi-Tech Engineering College, Gobichettipalayam, Erode

T.Thanagokul Department of EEE,

Shree Venkateshwara Hi-Tech Engineering College, Gobichettipalayam, Erode

The use of smart helmet technology is a creative solution that benefits both motorcyclists and society at large in many ways. Smart helmet technology can possibly save lives and lessen the strain on the healthcare system by lowering the likelihood of accidents and injuries on the road through features like alcohol detection, accident notifications, and helmet-wearing detection. Future smart helmet designs should bring forth even more sophisticated and useful features as technology develops and advances.


    Initially, the helmet will detect whether the helmet is worn or not. Then the alcohol sensor in the helmet will sense the alcohol consumption of the driver; if it is above the threshold limit, the sensor will send a signal to the bike unit, which controls the ignition of the bike, and the bike unit will send an alert message to the family and friends. In case of an accident, the acceleration sensor will sense the sudden dip in acceleration and sense that the accident has occurred, and the alert message will be delivered to the nearby hospital and family using the GSM and GPS modules. A voice assistant will help the rider with navigation and notification alerts.

    The block diagram given below outlines the major components and their interactions in the modern helmet project, showcasing the integration of sensors, communication modules, control elements, and user interfaces for a comprehensive and intelligent helmet system.

    Alcohol sensor





    Helmet switch

    The block diagram of the helmet unit is shown below:

    Fig.1 Block diagram of Helmet Unit






    5V RPS

    Micro- controller





    enhancing the reliability and accuracy of information exchange.

    Vehicle Ignition

    Fig.2 Block diagram of Vehicle Unit

    1. Alcohol sensor:

      The MQ-3 alcohol sensor is designed to detect the presence of alcohol vapours. In the context of a smart helmet, it can be employed as a safety measure to prevent users from operating the helmet under the influence of alcohol. Integration of the alcohol sensor enhances the overall safety features, ensuring that users are in a suitable condition to use the smart helmet and operate associated machinery or vehicles.

      Fig.3 Alcohol Sensor

      Fig.5 RF Encoder

      1. Decoder(HT12D):

        The Decoder, HT12D, complements the encoder by decoding the received signals. In wireless communication systems, data is often encoded before transmission for efficiency and security reasons. The HT12D decoder is used to decode these signals, allowing the microcontroller or other components to interpret and act upon the transmitted information. This pair of encoder and decoder can be essential in achieving secure and reliable wireless communication within the smart helmet system.

    2. Vibration sensor:

    The vibration sensor is integrated into the helmet to detect vibrations or sudden movements. This sensor plays a vital role in identifying potential accidents or collisions. Upon

    1. Microcontroller:

      Fig.6 RF Decoder

      detecting significant vibrations, the smart helmet can trigger emergency response mechanisms, such as sending alerts to predefined contacts, activating safety features, or recording incident data.

      Fig.4 Vibration Sensor

      c) Encoder (HT12E):

      The Encoder, specifically the HT12E, is a crucial component in the modern helmet project. It is responsible for encoding data before transmission, typically in scenarios where wireless communication is involved. In this context, the HT12E encoder may be used to encode signals or data from various sensors or the microcontroller before transmitting it wirelessly. This ensures that the transmitted data is in a format suitable for the communication protocol used,

      The microcontroller, specifically the ATMEGA 328, serves as the brain of the smart helmet. It processes data from various sensors, manages communication with external devices through GSM, interprets GPS location data, and controls motorized components using the motor driver. The microcontroller orchestrates the overall functionality of the smart helmet, ensuring seamless integration of its various components and enabling intelligent decision-making based on sensor inputs.

      Fig.7 ATMEGA 328 Microcontroller

    2. LCD Display:

      The 16×2 Alphanumeric LCD (Liquid Crystal Display) serves as the user interface for the smart helmet. It displays relevant information to the user, such as GPS coordinates, sensor readings, or system status. The 16×2 format indicates the display's capacity to show 16 characters in each of its two rows. The LCD enhances the user experience by providing real-time information, making the smart helmet more interactive and user-friendly.

      Fig.8 LCD Display

    3. GSM Module (SIM 800):

      For the smart helmet project, the GSM modulemore especially, the SIM 800is an essential part. By allowing the helmet to send and receive data over the cellular network, it makes communication easier. The smart helmet's SIM 800 GSM module allows it to send vital information to a selected contact or distant server, including position information, emergency warnings, and other pertinent data. Due to its ability to maintain connectivity even in places devoid of Wi- Fi, it is essential to improving the safety aspects of the helmet.

      Fig.9 GSM Module

    4. GPS Module (NEO 6M 0001)

      The GPS module, NEO 6M 0001 in this case, provides the smart helmet with accurate location data. This information is essential for various applications, such as tracking the user's position, mapping routes, and sending location-based alerts. The GPS module contributes to the overall functionality of the smart helmet by enabling features like real-time location tracking, geo-fencing, and navigation assistance.

      Fig.10 GPS Module

    5. Voltage regulator:

      The Voltage Regulator, specifically the LM7805, is a crucial part of the power supply system for the smart helmet. It regulates the voltage to a stable 5 volts, ensuring that the components within the helmet receive a consistent and reliable power supply. The LM7805 helps prevent damage to sensitive electronic components caused by voltage fluctuations and ensures optimal performance of the entire smart helmet system

      Fig.11 5V RPS

      There are various steps involved in creating a comprehensive flowchart that outlines every aspect of the modern helmet project. The key steps in using the modern helmet are shown in the simplified flowchart below:

      Fig.12 Flowchart


    The implementation of the smart helmet project has yielded promising results in enhancing user safety and incorporating intelligent features. The smart helmet successfully utilizes the GSM module for seamless cellular communication, providing real-time updates and emergency alerts. The GPS module enables precise location tracking and navigation assistance. The motor driver facilitates motorized components, ensuring optimal functionality. Vibration and alcohol sensors contribute to safety features by detecting potential accidents and preventing usage under the influence. The integration of the encoder and decoder ensures secure wireless communication, while the voltage regulator and diodes contribute to a stable power supply and efficient energy management. The 16×2 Alphanumeric LCD serves as an effective user interface, displaying relevant information.


    The smart helmet concept effectively combines a number of different parts to produce a complete and useful solution that aims to improve user convenience and safety. While the GPS module delivers precise location information, the GSM module guarantees dependable connection. By identifying possible mishaps or dangerous situations, sensors like the alcohol and vibration sensors enhance intelligent safety measures. The ATMEGA 328 microcontroller functions as the central processing unit, coordinating the interplay among various components to ensure smooth functioning. Secure wireless communication is facilitated by the encoder and decoder, and sensitive components are safeguarded and a stable power supply is maintained by the voltage regulator and diodes. The user is presented with pertinent information in real-time by the 16×2 Alphanumeric LCD, which also functions as an intuitive user interface.



    1. Abhinav Anand, Alcoholic detection, Department of Electronics and Telecommunications, IJEETC, 2015.

    2. Ashika Preethi. .S; Smart Attendance Monitoring System Using IOT, 2023, 9th International Conference on Advanced Computing and Communication System (ICACCS), IEEE DOI:10.1109/ICACCS57279.2023.10112850

    3. Ferreira, L.; Matos, E.L.; Menendez, L.M.; Mandado, E MILES: A Microcontroller Learning System combining Hardware and Software tools," Frontiers in Education, 2005. FIE '05. Proceedings 35th Annual Conference, vol., no., pp.F4E, 19-22 Oct. 2005

    4. Lee, Assessing the Feasibility of Vehicle-Based Sensors To Detect Alcohol Impairment. 2010, National Highway Traffic Safety Administration: Washington, DC.

    5. Manjesh N., Sudarshan Raj, Smart Helmet using GSM & GPS Technology for Accident detection and Reporting System, International Journal of Electrical and Electronics Research, 2, 4 (2014).

    6. Park, Sang-O; Lee, Kyeong-Ryong; Baek, Kwang-Je (2016). "The Preventive Effect of Head Injury by Helmet Type in Motorcycle Crashes: A Rural Korean Single-Center Observational Study". BioMed Research International. 2016.

    7. Thum Chia Chieh; Mustafa, M.M.; Hussain, A.; Zahedi, E.; Majlis, B.Y. " Driver fatigue detection using steering grip force," Research and Development, 2003. SCORED 2003. Proceedings. Student

    8. Vasan, S.S.; Gururaj, G. (2021). "Unhelmeted two- wheeler riders in India". The National Medical Journal of India. 34: 171172. doi:10.25259/NMJI_455_18

While the current version of the smart helmet project is robust, there are several areas for potential future development and improvement. One avenue for exploration is the integration of augmented reality (AR) features, which could enhance user experience by providing additional information and improving situational awareness. Additionally, implementing machine learning algorithms could enable more sophisticated data analysis, allowing the system to adapt to user behaviour and potentially predict and prevent accidents more effectively. Another area for enhancement is the incorporation of health monitoring sensors, which could allow the helmet to track vital signs and promptly notify emergency services or designated contacts in the event of a medical emergency. Expanding sensor capabilities to include temperature and air quality sensors could provide users with a more comprehensive understanding of their environment, further improving safety. Exploring advanced communication protocols or utilizing 5G connectivity could improve data transmission speed and reliability, leading to faster responses to critical situations. Finally, prioritizing improvements in helmet ergonomics and comfort could increase user satisfaction, potentially allowing for customizable features based on individual preferences.