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    Topic review

    Smart Helmet in Applied Sciences

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    Submitted by: Yosoon Choi

    Definition

    A smart helmet is a wearable device that has attracted attention in various fields, especially in applied sciences, 

    1. Introduction

    A wearable (electronic) device is a smart electronic device that can be planted on the body or worn with accessories. Since Google recently launched its head-mounted display, wearable devices have garnered a significant amount of attention [1]. Wearable devices have been able to take an important position in the home appliance market in a short period and are considered a new means of meeting the requirements of many industries. For example, the construction industry has studied the use of wearable devices in the workplace for health and safety management by close detection and physiological monitoring of construction workers [2]. The logistics industry has begun using wearable barcode scanner gloves to simplify work that does not involve hand use [3]. Some insurance companies encourage healthy eating habits and use wearable devices to improve the health of corporate workers [4].
    There are different types of smart wearable devices, such as helmets, watches, glasses, contact lenses, textiles, fabrics, headbands, beanies, caps, rings, bracelets, and earrings [5]. Among these, this study focused on smart helmets. Smart helmets include multiple electronic devices and sensors that help users gather real-time data and assist them in reducing operational risks and improving safety in the long run. The global smart helmet market size was valued at USD 372.4 million in 2018 and is expected to expand at a compound annual growth rate of 18.6% from 2019 to 2025 [6].
    Research on smart helmet applications is being conducted in various fields to improve safety and efficiency of motorcyclists [7] and workers [8][9]. For example, Singh et al. [7] studied the application of smart helmets to detect portholes and collect air quality data on roads. Wang et al. [8] detected stair fall by analyzing changes in weight support and pressure center using a smart helmet, and Mohammed et al. [9] used smart helmets to prevent the spread of coronavirus by measuring the body temperature and personal information of pedestrians. Like some of the examples mentioned earlier, many studies related to the development and application of smart helmets have been reported in the literature [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75][76][77][78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94][95][96][97][98][99][100][101][102][103][104][105][106][107][108][109]; however, no systematic review has been conducted to analyze the current status and trends of smart helmet research.
    The purpose of this study was to review the current status and trends of smart helmet research systematically. The current status of smart helmet research by year and application field were investigated by analyzing 103 academic research articles published in the past 11 years (2009–2020). The types of sensors, microcontrollers, and wireless communication technology were analyzed to identify the trends in smart helmet studies.

    2. Current Status of Publications Related to Smart Helmet Research by Year and Source

    The number of publications on smart helmets during the past 11 years is shown in Figure 2. In the first seven years (2009–2015), there were limited articles, with an average of 1.28 articles per year. In the next two years (2016 and 2017), the average number of publications increased to 8.5. In 2018, the number of publications more than doubled from the previous year’s average, surging to 21 publications. In 2019, there were 27 publications, and, in 2020, the number of publications was 29, making it the highest number for a year overall. The average number of publications in the last three years (2018–2020) was 25.6, which is nearly three times higher than the average number of publications in 2016 and 2017. Therefore, research on smart helmets has been extremely active recently. Additionally, the sources of publications were academic journals (55.3%) and conference proceedings (44.7%).
    Figure 1. Number of publications related to smart helmet research by (a) year and (b) source of publications.

    3. Application Fields of Smart Helmet Research

    The current status of smart helmet studies in each application field was analyzed to determine which fields were studying and utilizing smart helmets the most. The smart helmet applications were organized in two stages to observe the classification at a glance. In the first stage, the studies were classified into two categories (i.e., motorcyclists and workers) according to users of smart helmets. In the second stage, detailed application fields were added below the first stage, as shown in Figure 2. Figure 3 shows the cumulative number of publications on smart helmets during the past 11 years in the first stage of the classification criteria. As shown, studies on smart helmets for motorcyclists and workers have been increasing every year; however, the rate of increase is relatively faster for motorcyclists. This indicates that research on smart helmets for workers must be accelerated.
    Figure 2. Classification of application fields in smart helmet studies.
    Figure 3. Cumulative number of publications by year in bike, occupational safety, disaster prevention, and medicine fields.
    The applications of smart helmets for motorcyclists consist of 81 studies that account for the largest number of publications [7][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75][76][77][78][79][80]. These applications can be classified into four subcategories: start control, accident prevention, rescue request, and convenience improvement. Some studies fall under more than one subcategory when the developed smart helmet is used for various purposes by motorcyclists. Figure 4 shows the percentage of studies according to the subcategory. Note that most smart helmets for motorcyclists have been developed for the start control of motorcycles (42.3%) and rescue requests in the case of an accident (39.2%).
    Figure 4. Percentage of smart helmet studies for motorcyclists by sub-category.
    The application fields include mining, construction, petrochemistry, disaster prevention, and medical treatment. Figure 5 shows the percentage of smart helmet studies conducted in each application field.
    Figure 5. Percentage of smart helmet studies for workers by sub-category.
    Table 1. Summary of smart helmet applications for workers in the fields of mining, construction, petrochemistry, disaster prevention, medical treatment, etc.
    Reference Year Feature and High-Level Functionality Application
    (Sub-Category)
    Sensor Microcontroller Wireless Technology
    Wang et al. [8] 2020 Detects stair fall by analyzing changes in weight support and pressure center Construction Accident detection Single board MCU
    (Arduino)
    Bluetooth
    Mohammed et al. [9] 2020 Helps prevent the spread of coronavirus by measuring the body temperature and personal information of pedestrians Medical treatment Temperature detection Single board MCU
    (Arduino)
    Bluetooth
    Qiang et al. [90] 2009 Real-time monitoring of methane, temperature and humidity data and support for voice communication between operators Mining Harmful gas detection; Humidity detection; Temperature detection Chip MCU
    (S3C44BOX)
    ZigBee
    Shabina [91] 2014 Transmits real-time temperature, humidity, and fire data through a wireless network and alerts the operator by sounding an alarm when the threshold is reached Mining Temperature detection; Humidity detection; Fire detection Chip MCU
    (AT89S52)
    N/A
    Behr et al. [92] 2016 Collects data on the concentration of harmful gases, whether the helmet is worn, and the amount of impact on the helmet, and transmits and analyzes it to the cloud server Mining Harmful gas detection; Helmet wear detection Chip MCU
    (ATZB-24-A2)
    ZigBee
    Hazarika [93] 2017 Measures the concentration of harmful gas and sends it to the cloud server for real-time monitoring and alarms in the control room when the threshold is exceeded Mining Harmful gas detection Single board MCU
    (Arduino)
    ZigBee
    Sharma and Maity [94] 2018 Measures the concentration of harmful gases, temperature, and humidity, sends them to the cloud server for real-time monitoring, and sounds an alarm when the threshold is exceeded Mining Harmful gas detection; Temperature detection; Humidity detection Single board MCU
    (Arduino)
    ZigBee
    Revindran et al. [95] 2018 A wireless sensor network was built and rescue request was from nearby workers and medical teams when workers send distress messages Mining Accident detection Chip MCU
    (Arduino)
    RF
    Eldemerdash et al. [96] 2019 Temperature and humidity, harmful gas concentration, and pressure data are monitored, and when thresholds are reached, warnings are sent through LEDs and buzzers Mining Temperature detection; Humidity detection; Harmful gas detection Single board computer
    (Raspberry Pi)
    ZigBee
    Sanjay et al. [97] 2019 Temperature and humidity, harmful gas concentration, and pressure data are monitored, and when thresholds are reached, warnings are made through LEDs and buzzers Mining Temperature detection; Humidity detection; Harmful gas detection Single board MCU
    (Arduino)
    ZigBee
    Charde et al. [98] 2020 Collects harmful gas concentration, humidity, and temperature data to enable real-time monitoring and alerts through buzzer and LCD when hazardous concentrations are reached Mining Temperature detection; Humidity detection; Harmful gas detection Chip MCU
    (PIC)
    ZigBee
    Sujitha et al. [99] 2020 Detects temperature and humidity, light intensity, toxic gas levels in the air, traces of flames, etc. and warns when thresholds are exceeded Mining Temperature and Humidity detection; Brightness detection; Harmful gas detection; Fire detection Single board MCU
    (Arduino)
    WiFi
    Pirkl et al. [100] 2016 IR camera sensor measures the temperature of the surrounding environment Construction Temperature detection Chip MCU
    (IntelEdison)
    Bluetooth
    Lee et al. [101] 2019 Detects falls, air quality, and objects fall and sends data to the cloud server for storage Construction Harmful gas detection; Accident detection Single board MCU
    (Arduino)
    Bluetooth
    Li et al. [102] 2014 Inertia and brain waves are measured to analyze injury and fatigue, and vibration alerts when thresholds are exceeded General Brainwave detection; Motion detection Chip MCU
    (PIC)
    N/A
    Dhingra et al. [103] 2018 Voice communication between workers is possible and rescue request through panic button in case of crisis General Accident detection Single board MCU
    (Arduino)
    RF
    Aston et al. [104] 2020 Impulse quantity is dispersed General N/A Chip MCU N/A
    Campero-Jurado et al. [105] 2020 Temperature and humidity, harmful gas concentration and brightness are detected and transmitted to a cloud server for analysis General Temperature and Humidity detection; Brightness detection; Harmful gas detection Chip MCU
    (PIC)
    WiFi
    Shu et al. [106] 2015 Early warning in case of leakage of harmful gas Petrochemistry Harmful gas detection Smart device
    (Smartwatch)
    WiFi
    Bisio et al. [107] 2017 Detects stroke in emergency patients Medical treatment Brainwave detection Smart device
    (Smartphone)
    Bluetooth
    Shahiduzzaman et al. [108] 2019 Detects a fall, sends medical data to the medical cloud, and requests rescue Medical treatment Accident detection Smart device
    (Smartphone)
    Bluetooth
    Jeong et al. [109] 2018 Infrared image, optical image, drone image, oxygen residual amount, inertia, etc. are collected Disaster prevention Harmful gas detection Smart device
    (Smartwatch)
    WiFi
    In the mining industry, 10 studies were performed on a smart helmet that detects harmful gases, such as carbon monoxide (CO) and methane (CH4), and guarantees the safety of workers through rescue requests in the case of a dangerous situation [90][91][92][93][94][95][96][97][98][99]. Three studies have been reported in the construction industry, where smart helmets were primarily used to detect workplace hazards and provide risk alarms to construction workers [8][100][101]. For example, a safety helmet with gravity and head movement sensors was used at the construction site to detect a falling worker and activate emergency rescue requests [8]. Four studies on smart helmets were conducted to support voice communication between workers and warn them by detecting injuries in general manufacturing sites [102][103][104][105]. A smart helmet that ensures the safety of workers by warning the occurrence of harmful gas leaks was developed in the petrochemical industry [106].
    Three studies [9][107][108] on smart helmets were found in the medical field to improve the work efficiency of medical staff and ensure the safety of patients. In this application, a smart helmet worn by the medical staff was used to detect body temperature and brain waves in emergency situations [9][107]. A smart helmet was developed for medical staff to detect the body temperature of a pedestrian in real time. It was used to prevent coronavirus by warning them through an alarm when discovering a high-temperature pedestrian. Additionally, a study developed a smart helmet to prevent elderly patients lying in bed from falling [108]. One study reported in the literature dealt with a smart helmet for disaster prevention [109]. In this study, the smart helmet was used to support rescue workers at disaster sites.

    4. Sensors Used for Smart Helmet Applications

    Various sensors are attached to a smart helmet based on the application field and purpose. Table 2 shows the types of sensors used in smart helmet studies. The sensors can be broadly classified into three types: human health, environment, and machine monitoring. The cumulative number of sensor types used in smart helmet studies by year is illustrated in Figure 6a. The use of sensors to monitor human health is increasing every year. The frequency of use of environmental monitoring sensors has also increased in recent years. The percentages of sensor uses for each sensor type are shown in Figure 6b–d. For human health monitoring, the accident detection sensor accounts for 32%, followed by the helmet wear detection sensor and alcohol detection sensor with 30% and 27%, respectively. In the case of environmental monitoring, sensors for harmful gas detection, video shooting, and temperature detection each account for 23%. For the machine monitoring, the speed detection sensor occupies 70% and is the most used.
    Figure 6. Trend of sensor uses in smart helmet studies. (a) Cumulative number of uses of sensor types according to year. Usage percentage of sensors for (b) human health monitoring, (c) environmental monitoring, and (d) machine monitoring.
    Table 2. Types of sensor depending on the purpose used in smart helmet studies.
    Types of sensor depending on the purpose used in smart helmet studies.
    Human Health Monitoring Environmental Monitoring Machine Monitoring
    - Accident detection (50 papers)
    - Helmet wear detection (46 paper)
    - Alcohol detection (42 papers)
    - Drowsiness detection (6 papers)
    - Brainwave detection (4 papers)
    - Heart rate detection (4 papers)
    - Head motion detection (3 papers)
    - Harmful gas detection (11 papers)
    - Video shooting (11 papers)
    - Temperature detection (11 papers)
    - Humidity detection (7 papers)
    - Brightness detection (3 papers)
    - Barometric pressure detection (2 papers)
    - Fire detection (2 papers)
    - Pothole detection (1 papers)
    - Speed detection (7 papers)
    - Proximity warning (2 papers)
    - Fuel level detection (1 papers)

    5. Types of Microcontroller Used in Smart Helmets

    Different types of microcontroller have been used to develop smart helmets. By analyzing 103 articles, this study classified the microcontrollers into four categories.
    -
    Chip modular concept unit (MCU): a single computer chip designed for embedded applications (e.g., PIC 18F8720) [110]
    -
    Single-board MCU: a microcontroller built onto a single printed circuit board (e.g., Arduino) [111]
    -
    Single-board computer: a complete computer built on a single circuit board, with microprocessor(s), memory, input/output, and other features required for a functional computer (e.g., Raspberry Pi) [112]
    -
    Smart device: an electronic device, generally connected to other devices or networks by means of different wireless protocols that can operate to some extent interactively and autonomously (e.g., smartphone) [113]
    The number of studies that used each of the four types is presented in Figure 7. Among the 103 articles analyzed in this study, the single-board MCU was the most used (56 studies), followed by the chip MCU (28 studies). The number of single-board computers and smart devices used was relatively small (11 and 8 articles, respectively). The use of single-board MCUs has increased rapidly since 2016. Although there have not been many uses of single-board computers so far, their use for smart helmets has increased since 2017. The use of smart devices has been minimal, which is believed to be because of the relatively high cost compared with other devices.
    Figure 7. Cumulative number of microcontrollers used in smart helmet studies by year.
    Figure 8 shows the use of sensors according to the type of microcontroller in smart helmet studies. Accident, helmet wear, and alcohol detection sensors have been frequently used with the chip MCU and single-board MCU. As shown in Figure 6, the uses of accident, helmet wear, and alcohol detection sensors make up a large part of smart helmet applications. Therefore, it is judged that the uses of chip MCU and single-board MCU were rapidly increased due to the increased development of smart helmets for accident, helmet wear, and alcohol detections. In the case of using a sensor that processes a large amount of data such as video shooting, it can be seen that a single-board computer or a smart device is being used. If the use of sensors based on images or videos increases in smart helmet studies, the single-board computers or smart devices are expected to be used more as microcontrollers.
    Figure 8. Number of uses by sensor and microcontroller types in smart helmet studies.

    6. Types of Wireless Communication Technology Used in Smart Helmet Studies

    The data obtained from smart helmets can be transmitted to other smart devices or cloud servers using several wireless communication technologies. Of the 103 articles, 88 reported studies that used wireless communication technology, such as RF, Bluetooth, Wi-Fi, and Zigbee for this purpose, whereas the remaining did not. Figure 9 shows the cumulative number of uses of wireless communication technology by year for sharing data from smart helmets. According to the analysis results, RF and Bluetooth were the most commonly used, and the number of uses has been increasing rapidly since 2015. Zigbee has been used for the longest time; however, its usage has not increased significantly until recently.
    Figure 9. Cumulative number of wireless communication technologies used in smart helmet studies by year.
    The reason why RF and Bluetooth are used frequently is related to the microcontroller used in smart helmet applications. Until now, the chip MCU and single-board MCU have been mainly used for smart helmet development, and these two types of microcontrollers often use RF and Bluetooth as shown in Figure 10. In the future, as the use of single-board computers increases, the frequency of use of Wi-Fi is expected to increase. In addition, the uses of Bluetooth and Wi-Fi may increase when the use of smart devices increases in smart helmet studies.
    Figure 10. Number of uses by wireless communication technology and microcontroller types in smart helmet studies.

    The entry is from 10.3390/app11115039

    References

    1. Wrzesińska, N. The use of smart glasses in healthcare—Review. MEDtube Sci. 2015, 3, 31–34.
    2. Choi, B.; Hwang, S.; Lee, S.H. What drives construction workers’ acceptance of wearable technologies in the workplace? Indoor localization and wearable health devices for occupational safety and health. Autom. Constr. 2017, 84, 31–41.
    3. Audi Uses Wearables in Logistics. Available online: (accessed on 5 February 2018).
    4. TECHZONE360. Available online: (accessed on 20 November 2017).
    5. Wright, R.; Keith, L. Wearable Technology: If the Tech Fits, Wear It. J. Electron. Resour. Med Libr. 2014, 11, 204–216.
    6. Grand View Research. Available online: (accessed on 7 October 2020).
    7. Singh, V.; Chandna, H.; Upadhyay, N. SmartPPM: An Internet of Things Based Smart helmet Design for Potholes and Air Pollution Monitoring. EAI Endorsed Trans. Internet Things 2019, 5, 1–9.
    8. Wang, C.; Kim, Y.; Kim, D.G.; Lee, S.H.; Min, S.D. Smart helmet and Insole Sensors for Near Fall Incidence Recognition during Descent of Stairs. Appl. Sci. 2020, 10, 2262.
    9. Mohammed, M.N.; Syamsudin, H.; Al-Zubaidi, S.; Yusuf, E. Novel Covid-19 Detection and Diagnosis System Using Iot Based Smart Helmet. Int. J. Psychosoc. Rehabil. 2020, 24, 2296–2303.
    10. Rasli, M.K.A.; Madzhi, N.K.; Johari, J. Smart Helmet with Sensors for Accident Prevention. In Proceedings of the 2013 International Conference on Electrical, Electronics and System Engineering (ICEESE), Kuala Lumpur, Malaysia, 4–5 December 2013; pp. 21–26.
    11. Vijayan, S.; Govind, V.T.; Mathews, M.; Surendran, S. Alcohol Detection Using Smart Helmet System. Int. J. Emerg. Technol. Comput. Sci. Electron. 2014, 8, 190–195.
    12. Agarwal, N.; Singh, A.K.; Singh, P.P.; Sahani, R. Smart helmet. Int. Res. J. Eng. Technol. 2015, 2, 19–22.
    13. Gautam, A.S.; Dubey, G.K.; Mishra, M.; Prabhat, M. Smart helmet System. J. Emerg. Technol. Innov. Res. 2015, 2, 1165–1168.
    14. Melcher, V.; Diederichs, F.; Maestre, R.; Hofmann, C.; Nacenta, J.-M.; van Gent, J.; Kusić, D.; Žagar, B. Smart Vital Signs and Accident Monitoring System for Motorcyclists Embedded in Helmets and Garments for Advanced ECall Emergency Assistance and Health Analysis Monitoring. Procedia Manuf. 2015, 3, 3208–3213.
    15. Chandran, S.; Chandrasekar, S.; Elizabeth, N.E. Konnect: An Internet of Things (IoT) Based Smart helmet for Accident Detection and Notification. In Proceedings of the 2016 IEEE Annual India Conference (INDICON), Bangalore, India, 16–18 December 2016; pp. 1–4.
    16. Magno, M.; D’Aloia, A.; Polonelli, T.; Spadaro, L.; Benini, L. SHelmet: An Intelligent Self-Sustaining Multi Sensors Smart helmet for Bikers. In Sensor Systems and Software; Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Magno, M., Ferrero, F., Bilas, V., Eds.; Springer International Publishing: Cham, Switzerland, 2017; Volume 205, pp. 55–67.
    17. Nikharge, B.J.; Poojary, M.M.; Pooja, T. Smart Helmet—Intelligent Safety for Motorcyclist Using Raspberry Pi and Open Cv. Int. Res. J. Eng. Technol. 2016, 3, 589–593.
    18. Jadhawar, M.; Kandepalli, G.; Kohade, A.; Komati, R. Smart Helmet Safety System Using Atmega 32. Int. J. Res. Eng. Technol. 2016, 5, 287–289.
    19. Kim, J.; Koo, S.E.; Lim, J.Y.; Jin, M.W.; Choi, J.M. Smart Helmet. In Proceedings of the ICCC 2016 International Conference on Convergence Content, Kunsan, Korea, 22–27 May 2016; pp. 357–358.
    20. Kumar, S.; Srikrishnan, A.; Ravi, S. Cloud Incorporated Smart helmet Integrated with Two-Wheeler Communication Setup. Int. J. Control. Theory Appl. 2016, 9, 251–261.
    21. Vashisth, R.; Gupta, S.; Jain, A.; Gupta, S.; Sahil; Rana, P. Implementation and Analysis of Smart helmet. In Proceedings of the 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC), Solan, India, 21–23 September 2017; pp. 111–117.
    22. Varade, A.; Gajbhiye, N.; Panchbhai, A.V.V. Smart Helmet Using GSM and GPS. Int. Res. J. Eng. Technol. 2017, 04, 1662–1667.
    23. Rajput, A.; Saxena, A.; Agarwal, A.; Bhatia, A.; Mishra, A. Smart helmet with Rider Safety System. Int. J. Innov. Emerg. Res. Eng. 2017, 4, 52–60.
    24. Patel, M.V.A.; Mishra, M.A.; Hiten, M.R.; Prajapati, M.K. Smart helmet. Int. Res. J. Eng. Technol. 2017, 4, 7–10.
    25. Muthiah, M.; Aswin Natesh, V.; Sathiendran, R.K. Smart helmets for Automatic Control of Headlamps. In Proceedings of the 2015 International Conference on Smart Sensors and Systems (IC-SSS), Bangalore, India, 21–23 December 2015; pp. 1–4.
    26. Ahuja, P.; Bhavsar, K. Microcontroller Based Smart helmet Using GSM & GPRS. In Proceedings of the 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, 11–12 May 2018; pp. 1–9.
    27. Godwani, P.D.; Dhokrat, A.U.; Kubde, G.D.; Kumbhar, R.R.; Mahajan, R.G. Smart helmet for Accident Detection and Navigation. Int. J. Creat. Res. Thoughts 2018, 6, 788–792.
    28. Parameshwari, P.; Pujari, V.; Gadgay, B. Smart Helmet for Accident Prevention. Int. Res. J. Eng. Technol. 2018, 5, 368–370.
    29. Biswas, J.R.; Kachroo, S.; Chopra, P.; Sharma, S. Development of an App Enabled Smart helmet for Real Time Detection and Reporting of Accidents. In Proceedings of the 2018 7th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions (ICRITO), Noida, India, 29–31 August 2018; pp. 703–708.
    30. Budiman, A.R.; Sudiharto, D.W.; Brotoharsono, T. The Prototype of Smart helmet with Safety Riding Notification for Motorcycle Rider. In Proceedings of the 2018 3rd International Conference on Information Technology, Information System and Electrical Engineering (ICITISEE), Yogyakarta, Indonesia, 13–14 November 2018; pp. 362–367.
    31. Uniyal, M.; Rawat, H.; Srivastava, M.; Srivastava, V.K. IOT Based Smart helmet System with Data Log System. In Proceedings of the 2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), Greater Noida, India, 12–13 October 2018; pp. 28–31.
    32. Paulchamy, D.B.; Sundhararajan, C.; Xavier, R.; Ramkumar, A.; Vigneshwar, D. Design of Smart helmet and Bike Management System. Asian J. Appl. Sci. Technol. 2018, 2, 207–211.
    33. Souza, A.D.; Maliyackal, S.S. Helmet Integrated Bike Ignition Using Arduino. In Proceedings of the 4th International Conference on Energy Efficient Technologies for Sustainability–ICEETS’18, Tamil Nadu, India, 5–7 April 2018; pp. 1–5.
    34. Nanda, S.; Joshi, H.; Khairnar, S. An IOT Based Smart System for Accident Prevention and Detection. In Proceedings of the 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), Pune, India, 16–18 August 2018; pp. 1–6.
    35. Deva Kumar, S.V.S.V.P.; Akashe, S.; Kumar, V. Advanced Control of Switching Ignition by Smart helmet. Int. J. Image Graph. Signal Process. 2018, 10, 34–42.
    36. Sumamah, M.; Faiz, M.; Tyagi, A. Smart helmet kit. Int. Res. J. Eng. Technol. 2018, 5, 3018–3020.
    37. Shabbeer, S.A.; Meleet, M. Smart helmet for Accident Detection and Notification. In Proceedings of the 2017 2nd International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS), Bengaluru, India, 21–23 December 2017; pp. 1–5.
    38. Gudavalli, D.K.P.; Rani, B.S.; Sagar, C.V. Helmet Operated Smart E-Bike. In Proceedings of the 2017 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), Srivilliputhur, India, 23–25 March 2017; pp. 1–5.
    39. Tapadar, S.; Ray, S.; Saha, H.N.; Saha, A.K.; Karlose, R. Accident and Alcohol Detection in Bluetooth Enabled Smart helmets for Motorbikes. In Proceedings of the 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 8–10 January 2018; pp. 584–590.
    40. Premalatha, K.; Nandhini, J.J. Safeguarding Two Wheeler User’s Lives Using Smart helmet. Int. J. Innov. Technol. Explor. Eng. 2018, 8, 417–419.
    41. Dhulavvagol, P.M.; Shet, R.; Nashipudi, P.; Meti, A.S.; Ganiger, R. Smart helmet with Cloud GPS GSM Technology for Accident and Alcohol Detection. In Cognitive Computing and Information Processing; Communications in Computer and Information Science; Nagabhushan, T.N., Aradhya, V.N.M., Jagadeesh, P., Shukla, S.M.L.C., Eds.; Springer: Singapore, 2018; Volume 801, pp. 346–357.
    42. Joshi, S.B.; Joshi, A.S. A Novel Method for Safety of Two Wheeler Using Microcontroller. Int. J. Adv. Res. Innov. Ideas Educ. 2019, 5, 1439–1442.
    43. Namayala, P.P. Development of Smart helmet Motor Cycles’ Embedded System. Int. J. Eng. Res. Adv. Technol. 2019, 5, 75–84.
    44. Wong, K.I.; Chen, Y.-C.; Lee, T.-C.; Wang, S.-M. Head Motion Recognition Using a Smart helmet for Motorcycle Riders. In Proceedings of the 2019 International Conference on Machine Learning and Cybernetics (ICMLC), Kobe, Japan, 7–10 July 2019; pp. 1–7.
    45. Kinage, V.; Patil, P. IoT Based Intelligent System for Vehicle Accident Prevention And Detection At Real Time. In Proceedings of the 2019 IoThird International conference on I-SMACT in Social, Mobile, Analytics and Cloud (I-SMAC), Palladam, India, 12–14 December 2019; pp. 409–413.
    46. Swathi, S.J.; Raj, S.; Devaraj, D. Microcontroller and Sensor Based Smart Biking System for Driver’s Safety. In Proceedings of the 2019 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), Tamilnadu, India, 11–13 April 2019; pp. 1–5.
    47. Reddy, D.D.V.; Suresh, V.; Hemalatha, T. Smart helmet and Bike Management System. J. Gujarat Res. Soc. 2019, 21, 303–311.
    48. Shravya, K.; Mandapati, Y.; Keerthi, D.; Harika, K.; Senapati, R.K. Smart helmet for Safe Driving. E3S Web Conf. 2019, 87, 1–4.
    49. Kanimozhi, L.; Sambasivam, R.; Pragathi, M.; Ranjith, M. Smart helmet with Accident Avoidance System. Cikitusi J. Multidiscip. Res. 2019, 6, 1–7.
    50. Patil, M.S.A.; Wagh, M.V.R.; Ganpatre, M.V.J. IOT Based Smart helmet For Accident Detection. Resincap J. Sci. Eng. 2019, 3, 455–458.
    51. Jesudoss, A.; Vybhavi, R.; Anusha, B. Design of Smart helmet for Accident Avoidance. In Proceedings of the 2019 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 4–6 April 2019; pp. 0774–0778.
    52. Kabilan, M.; Monish, S.; Siamala Devi, D.S. Accident Detection System Based on Internet of Things (IoT)-Smart helmet. Int. J. Eng. Res. Adv. Technol. 2019, 5, 154–157.
    53. Ashwin, M.; Yashwanth Gowda, S. Smart helmet Using GPS and GSM Modem. Int. J. Eng. Res. Adv. Technol. 2019, 8, 3005–3008.
    54. Chen, Y.-R.; Tsai, C.-M.; Wong, K.-I.; Lee, T.-C.; Loh, C.-H.; Ying, J.-C.; Chen, Y.-C. Motorcyclists’ Head Motions Recognition by Using the Smart helmet with Low Sampling Rate. In Proceedings of the 2019 Twelfth International Conference on Ubi-Media Computing (Ubi-Media), Bali, Indonesia, 5–8 August 2019; pp. 157–163.
    55. Gupta, S.; Sharma, K.; Salvekar, N.; Gajra, A. Implementation of Alcohol and Collision Sensors in a Smart helmet. In Proceedings of the 2019 Conception of smart iol helmet in smart factory (ICNTE), Navi Mumbai, India, 4–5 January 2019; pp. 1–5.
    56. Priya, V.; Dhanasekar, J.; Vasumathi, G. Smart helmet Using PIC Controller. Int. J. Eng. Res. Adv. Technol. 2019, 8, 750–752.
    57. Vijayakumar, D.; Ramesh, G.; Jayabalan, C.; Palani, S.; Selvam, M. Micro Controller Based Smart helmet by Ir Motion Sensors. Int. J. Eng. Res. Adv. Technol. 2019, 8, 1850–1853.
    58. Divyasudha, N.; Arulmozhivarman, P.; Rajkmumar, E.R. Analysis of Smart helmets and Designing an IoT Based Smart helmet: A Cost Effective Solution for Riders. In Proceedings of the 2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT), Chennai, India, 25–26 April 2019; pp. 1–4.
    59. Mhatre, K.; Nandwadekar, R.; Patil, A.; Shinde, R.; Kamble, P. Smart helmet With Intercom Feature. SSRN J. 2020, 1–5.
    60. Lakshmanachari, S.; Ramya, M. Smart helmet System for Identification of Road Accident Using Internet of Things. Int. J. Adv. Sci. Technol. 2020, 29, 1070–1076.
    61. Merlin, R.; Pranay, R.D. Smart helmet system. TEST Eng. Manag. 2020, 83, 1991–1995.
    62. Chidambarathanu, G.V.; Farzana, D.F.; Gowrishankar, J. Accidents Preventing Smart helmet Using EEG Sensor. TEST Eng. Manag. 2020, 82, 2541–2547.
    63. Santhanakrishnan, C.; Sharma, D.; Vashistha, A. Smart helmet for Rider (SHR) and Accident Detection Using IOT. Int. J. Adv. Sci. Technol. 2020, 29, 50–57.
    64. Sai Kumar, M.; Aruna, M. Third Eye Two Wheeler: Accident and Malt Detection in Bluetooth Enabled Smart helmets with Load Monitoring for Motorbikes. TEST Eng. Manag. 2020, 82, 6696–6701.
    65. Suman, A.; Parashar, A.; Shukla, A.; Shobha, K.R. Aagaahi—A Smart helmet. In Proceedings of the 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), Bangalore, India, 2–4 July 2020; pp. 1–6.
    66. Ahmed, S.U.; Uddin, R.; Affan, M. Intelligent Gadget for Accident Prevention: Smart helmet. In Proceedings of the 2020 International Conference on Computing and Information Technology (ICCIT-1441), Tabuk, Saudi Arabia, 9–10 September 2020; pp. 1–4.
    67. Dubey, S.; Meghana, K.; Likhitha, M.; Gupta, K.; Balaji, R. An Experimental Study on Advanced Lane Changing Signal Assist Technology with Smart helmet. Mater. Today Proc. 2020, 33, 4771–4776.
    68. Lokeshwaran, M.; Nikhit Mathew, S.P.; Joshuva, A. Raphael—The Smart helmet. In Proceedings of the 2020 International Conference on Wireless Comunications Signal Processing and Networking (WiSPNET), Chennai, India, 19–21 March 2020; pp. 48–51.
    69. Rahman, M.A.; Ahsanuzzaman, S.M.; Rahman, I.; Ahmed, T.; Ahsan, A. IoT Based Smart helmet and Accident Identification System. In Proceedings of the 2020 IEEE Region 10 Symposium (TENSYMP), Dhaka, Bangladesh, 5–7 June 2020; pp. 14–17.
    70. Faikul, U.; Hairil, B.; Ach, D. Smart helmet Control System Using Heart Pulse Indicator. In Proceedings of the 2020 International Conference on Science and Technology, Surabaya, Indonesia, 3 November 2020; pp. 1–8.
    71. Rao, P.K.; Sai, P.T.; Kumar, N.V.; Sagar, S.Y.V. Design and Implementation of Smart helmet Using IoT. In Proceedings of the 2020 International Confernce of Advance Research and Innovation, Meerut, India, 19 January 2020; pp. 323–325.
    72. Oviyaa, M.; Renvitha, P.; Swathika, R.; Paul, I.J.L.; Sasirekha, S. Arduino Based Real Time Drowsiness and Fatigue Detection for Bikers Using Helmet. In Proceedings of the 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Bangalore, India, 5–7 March 2020; pp. 573–577.
    73. Shahare, B.; Chawde, S.; Gudafwar, R.; Pal, H.; Bobade, P. Iot Based Smart Motor Cycle Helmet. Int. J. Progress. Res. Sci. Eng. 2020, 1, 107–109.
    74. Ashwini, S.S.; Udupa, N.G.; Sweta, N.; Alam, M.S. A Smart Helmet on IoT Technology for Safety and Accident Detection. Int. J. R D Eng. Sci. Manag. 2020, 3, 99–102.
    75. Jayasinghe, S.; Arachchige, U. A Smart helmet with a built-in drowsiness and alcohol detection system. J. Res. Technol. Eng. 2020, 1, 76–81.
    76. Aravinda, N.L.; Jabirullah, M.; DubasiKirtana. An Intelligent Helmet System Using IoT and Raspberry Pi. IOP Conf. Ser. Mater. Sci. Eng. 2020, 981, 1–7.
    77. MohanaRoopa, D.Y.; Soujanya, N.; Vaishnavi, V.S.; Vardhan, U.V. An IOT Based Smart helmet for Accident Detection and Notification. J. Interdiscip. Cycle Res. 2020, 7, 1–7.
    78. Pothirajan, M.G.; Mary, M.J.V. IOT Based Vehicle Monitoring Using Smart Helmet. Alochana Chakra J. 2020, 15, 671–674.
    79. Swarna, V.; Deepika, P.; Zaheer, S.; Raj, S.M.; Rao, E.K. Smart helmet for Rider’s Safety. J. Res. Sci. Eng. Manag. 2020, 6, 13–17.
    80. Parakkal, S.A.; Avhad, P.V.; Dhole, V.; Raikar, Y.; Gite, B.B. Smartphone Integrated Smart helmet for Real-Time Detection, Prevention and Reporting of Accidents. Bull. Monum. 2020, 21, 41–45.
    81. Kumar Kar, S.; Anshuman, D.A.; Raj, H.; Pall Singh, P. New Design and Fabrication of Smart helmet. IOP Conf. Ser. Mater. Sci. Eng. 2018, 402, 1–10.
    82. Rahman, A.; Abdurohman, M.; Putrada, A.G. Indicator Warning Refined Fuel Oil in A Motorcycle With Fuzzy Logic and Sound Navigaiotn Through Smart helmet. In Proceedings of the 2019 International Symposium on Electronics and Smart Devices (ISESD), Badung, Indonesia, 8–9 October 2019; pp. 1–5.
    83. Jadhav, A.; Rajput, S.; Baburao, K.V.; Rajput, D.D.S. Smart helmet Using Natural Language Processing, Head Mounted Display and Solar Panel. Int. J. Sci. Technol. Res. 2019, 8, 331–527.
    84. Youssef, A.; Colon, J.; Mantzios, K.; Gkiata, P.; Mayor, T.; Flouris, A.; De Bruyne, G.; Aerts, J.-M. Towards Model-Based Online Monitoring of Cyclist’s Head Thermal Comfort: Smart helmet Concept and Prototype. Appl. Sci. 2019, 9, 3170.
    85. Rao, S. Voice Controlled Wiper for Smart helmets. Int. J. Innov. Technol. Explor. Eng. 2019, 8, 2086–2089.
    86. Kanetkar, S.; Rathore, A.; Maheshwari, K.; Dubey, P.; Saxena, A. Smart helmet Wiper. In Proceedings of the 2020 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), Bhopal, India, 22–23 February 2020; pp. 1–4.
    87. Aatif, M.K.A.; Manoj, A. Smart helmet Based on IoT Technology. Int. J. Res. Appl. Sci. Eng. Technol. 2017, 5, 409–413.
    88. Ajay, A.; Vishnu, G.; Kishoreswaminathan, V.; Vishwanth, V.; Srinivasan, K.; Jeevanantham, S. Accidental Identification and Navigation System in Helmet. In Proceedings of the 2017 International Conference on Nextgen Electronic Technologies: Silicon to Software (ICNETS2), Chennai, India, 23–25 March 2017; pp. 202–204.
    89. Kumar, A.; Manjunath, S.S.; Monish, R.; Ramya, S. The Intercom Enabled Helmet. Int. Res. J. Eng. Technol. 2019, 6, 3986–3988.
    90. Qiang, C.; Ji-ping, S.; Zhe, Z.; Fan, Z. ZigBee Based Intelligent Helmet for Coal Miners. In Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering, Los Angeles, CA, USA, 31 March–2 April 2009; pp. 433–435.
    91. Shabina, S. Smart helmet Using RF and WSN Technology for Underground Mines Safety. In Proceedings of the 2014 International Conference on Intelligent Computing Applications, Coimbatore, India, 6–7 March 2014; pp. 305–309.
    92. Behr, C.J.; Kumar, A.; Hancke, G.P. A Smart helmet for Air Quality and Hazardous Event Detection for the Mining Industry. In Proceedings of the 2016 IEEE International Conference on Industrial Technology (ICIT), Taipei, Taiwan, 14–17 March 2016; pp. 2026–2031.
    93. Hazarika, P. Implementation of Smart Safety Helmet for Coal Mine Workers. In Proceedings of the 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), Delhi, India, 4–6 July 2016; pp. 1–3.
    94. Sharma, M.; Maity, T. Low Cost Low Power Smart helmet for Real-Time Remote Underground Mine Environment Monitoring. Wirel. Pers Commun. 2018, 102, 149–162.
    95. Revindran, R.; Vijayaraghavan, H.; Huang, M.-Y. Smart helmets for Safety in Mining Industry. In Proceedings of the 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore, India, 19–22 September 2018; pp. 217–221.
    96. Eldemerdash, T.; Abdulla, R.; Jayapal, V.; Nataraj, C.; Abbas, K. Iot Based Smart helmet for Mining Industry Application. Int. J. Adv. Sci. Technol. 2020, 29, 373–387.
    97. Sanjay, B.S.; Dilip, K.A.; Balasaheb, T.A.; KinnuKumar, S.; Saware, N.P. Smart helmet Using Zigbee. Int. J. Innov. Res. Technol. 2019, 6, 144–148.
    98. Charde, A.; Dehankar, B.; Ghaturle, S.; Bende, B.; Kitey, S. A Smart and Secured Helmet for Coal Mining Workers. J. Res. Appl. Sci. Eng. Technol. 2020, 8, 673–675.
    99. Sujitha, S.; Loret, S.; Gethsy, M. IOT Based Smart Mine Safety System Using Arduino. Int. J. Comput. Sci. Mob. Comput. 2020, 9, 141–145.
    100. Pirkl, G.; Hevesi, P.; Amarislanov, O.; Lukowicz, P. Smart helmet for Construction Site Documentation and Work Support. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Heidelberg, Germany, 12–16 September 2016; pp. 349–352.
    101. Lee, A.; Moon, J.; Min, S.D.; Sung, N.-J.; Hong, M. Safety Analysis System Using Smart helmet. Internet Comput. Internet Things 2019, 503, 102–107.
    102. Li, P.; Meziane, R.; Otis, M.J.-D.; Ezzaidi, H.; Cardou, P. A Smart Safety Helmet Using IMU and EEG Sensors for Worker Fatigue Detection. In Proceedings of the 2014 IEEE International Symposium on Robotic and Sensors Environments (ROSE), Timisoara, Romania, 16–18 October 2014; pp. 55–60.
    103. Dhingra, J.; Arora, G.; Bhatia, P.; Goel, C. Smart helmet with Inter-Communication System, Smart Reminder System and Panic Button for Emergencies. Int. J. Eng. Res. 2018, 7, 319–320.
    104. Aston, J.P.; Benko, N.; Truong, T.; Zaki, A.; Olsen, N.; Eshete, E.; Luttmer, N.G.; Coats, B.; Minor, M.A. Optimization of a Soft Robotic Bladder Array for Dissipating High Impact Loads: An Initial Study in Designing a Smart helmet. In Proceedings of the 2020 3rd IEEE International Conference on Soft Robotics (RoboSoft), New Haven, CT, USA, 15 May–15 July 2020; pp. 607–614.
    105. Campero-Jurado, I.; Márquez-Sánchez, S.; Quintanar-Gómez, J.; Rodríguez, S.; Corchado, J.M. Smart helmet 5.0 for Industrial Internet of Things Using Artificial Intelligence. Sensors 2020, 20, 6241.
    106. Shu, L.; Li, K.; Zen, J.; Li, X.; Sun, H.; Huo, Z.; Han, G. A Smart helmet for Network Level Early Warning in Large Scale Petrochemical Plants. In Proceedings of the 14th International Conference on Information Processing in Sensor Networks—IPSN ’15; ACM Press: Seattle, WA, USA, 2015; pp. 390–391.
    107. Bisio, I.; Fedeli, A.; Lavagetto, F.; Pastorino, M.; Randazzo, A.; Sciarrone, A.; Tavanti, E. Mobile Smart helmet for Brain Stroke Early Detection through Neural Network-Based Signals Analysis. In Proceedings of the GLOBECOM 2017—2017 IEEE Global Communications Conference, Singapore, 4–8 December 2017; pp. 1–6.
    108. Shahiduzzaman, K.M.; Hei, X.; Guo, C.; Cheng, W. Enhancing Fall Detection for Elderly with Smart helmet in a Cloud-Network-Edge Architecture. In Proceedings of the 2019 IEEE International Conference on Consumer Electronics—Taiwan (ICCE-TW), Yilan, Taiwan, 20–22 May 2019; pp. 1–2.
    109. Jeong, M.; Lee, H.; Bae, M.; Shin, D.-B.; Lim, S.-H.; Lee, K.B. Development and Application of the Smart helmet for Disaster and Safety. In Proceedings of the 2018 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, Korea, 17–19 October 2018; pp. 1084–1089.
    110. Wikipedia. Microcontroller. Available online: (accessed on 25 February 2021).
    111. Wikipedia. Single-Board Microcontroller. Available online: (accessed on 25 February 2021).
    112. Wikipedia. Single-Board Computer. Available online: (accessed on 25 February 2021).
    113. Wikipedia. Smart Device. Available online: (accessed on 25 February 2021).
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