Relevant bibliographies by topics / Wireless helmets

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Wireless helmets'

Author: Grafiati
Published: 28 May 2022
Last updated: 29 May 2022

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Journal articles on the topic "Wireless helmets"

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Choi, Yosoon, and Yeanjae Kim. "Applications of Smart Helmet in Applied Sciences: A Systematic Review." Applied Sciences 11, no. 11 (2021): 5039. http://dx.doi.org/10.3390/app11115039.

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A smart helmet is a wearable device that has attracted attention in various fields, especially in applied sciences, where extensive studies have been conducted in the past decade. In this study, the current status and trends of smart helmet research were systematically reviewed. Five research questions were set to investigate the research status of smart helmets according to the year and application field, as well as the trend of smart helmet development in terms of types of sensors, microcontrollers, and wireless communication technology. A total of 103 academic research articles published in the past 11 years (2009–2020) were analyzed to address the research questions. The results showed that the number of smart helmet applications reported in literature has been increasing rapidly since 2018. The applications have focused mostly on ensuring the safety of motorcyclists. A single-board-based modular concept unit, such as the Arduino board, and sensor for monitoring human health have been used the most for developing smart helmets. Approximately 85% of smart helmets have been developed to date using wireless communication technology to transmit data obtained from smart helmets to other smart devices or cloud servers.
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Li, Bin, Bo Li, and Hong Ze Yang. "Design and Study of the Initial Probe for Multi-Function Fire Helmet." Key Engineering Materials 458 (December 2010): 87–92. http://dx.doi.org/10.4028/www.scientific.net/kem.458.87.

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Fire helmets are important personal protective equipment for firemen in fire-fighting and rescue work, and the design of its function, structure, shape, etc. is directly related to the personal safety of the firemen. The development of the fire helmet with the modernized multi-function has very important significance. Through a study for the current research status and characteristics of fire helmets products in domestic and abroad, and looked into the developing trends of the fire helmet. Based on safety ergonomics and product system design method , a design program of multi-function fire helmet is proposed, which combined with the function of infrared thermal imaging, wireless communications conduction, emergency oxygen etc. it provided the design basis for related design and research in future.
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Li, Bo, Bin Li, and Hong Ze Yang. "Preliminary Studies on the Functional and Structural Design of Forest Fire Helmet." Advanced Materials Research 228-229 (April 2011): 605–9. http://dx.doi.org/10.4028/www.scientific.net/amr.228-229.605.

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In order to improve the performance of forest fire protection equipment, this paper proposes a new design concept of modern forest fire helmet. The scheme combines the functions of infrared thermal imaging, wireless communication and emergency oxygen making, which not only meets the security requirements in firemen’s present working, but also accords with the development of fire helmets at home and abroad. This helmet adopts the design conception of integration structurally, its weight and operation difficulty are both reduced, at the same time, accords with the Man-Machine Engineering. Moreover, using the three-dimensional processing software, this study realizes a simulation model of the designed forest fire helmet.
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Birli, Joseph. "Wireless communication systems for masks or helmets." Journal of the Acoustical Society of America 122, no. 5 (2007): 2505. http://dx.doi.org/10.1121/1.2801802.

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Gehlot, Anita, Rajesh Singh, Piyush Kuchhal, et al. "WPAN and IoT Enabled Automation to Authenticate Ignition of Vehicle in Perspective of Smart Cities." Sensors 21, no. 21 (2021): 7031. http://dx.doi.org/10.3390/s21217031.

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Currently, two-wheelers are the most popular mode of transportation, driven by the majority the people. Research by the World Health Organization (WHO) identifies that most two-wheeler deaths are caused due to not wearing a helmet. However, the advancement in sensors and wireless communication technology empowers one to monitor physical things such as helmets through wireless technology. Motivated by these aspects, this article proposes a wireless personal network and an Internet of Things assisted system for automating the ignition of two-wheelers with authorization and authentication through the helmet. The authentication and authorization are realized with the assistance of a helmet node and a two-wheeler node based on 2.4 GHz RF communication. The helmet node is embedded with three flex sensors utilized to experiment with different age groups and under different temperature conditions. The statistical data collected during the experiment are utilized to identify the appropriate threshold value through a t-test hypothesis for igniting the two-wheelers. The threshold value obtained after the t-test is logged in the helmet node for initiating the communication with the two-wheeler node. The pairing of the helmet node along with the RFID key is achieved through 2.4 GHZ RF communication. During real-time implementation, the helmet node updates the status to the server and LABVIEW data logger, after wearing the helmet. Along with the customization of hardware, a LABVIEW data logger is designed to visualize the data on the server side.
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Rowson, Steven, Jonathan G. Beckwith, Jeffrey J. Chu, Daniel S. Leonard, Richard M. Greenwald, and Stefan M. Duma. "A Six Degree of Freedom Head Acceleration Measurement Device for Use in Football." Journal of Applied Biomechanics 27, no. 1 (2011): 8–14. http://dx.doi.org/10.1123/jab.27.1.8.

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The high incidence rate of concussions in football provides a unique opportunity to collect biomechanical data to characterize mild traumatic brain injury. The goal of this study was to validate a six degree of freedom (6DOF) measurement device with 12 single-axis accelerometers that uses a novel algorithm to compute linear and angular head accelerations for each axis of the head. The 6DOF device can be integrated into existing football helmets and is capable of wireless data transmission. A football helmet equipped with the 6DOF device was fitted to a Hybrid III head instrumented with a 9 accelerometer array. The helmet was impacted using a pneumatic linear impactor. Hybrid III head accelerations were compared with that of the 6DOF device. For all impacts, peak Hybrid III head accelerations ranged from 24 g to 176 g and 1,506 rad/s2to 14,431 rad/s2. Average errors for peak linear and angular head acceleration were 1% ± 18% and 3% ± 24%, respectively. The average RMS error of the temporal response for each impact was 12.5 g and 907 rad/s2.
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Rudrawar, Mangesh, Shivam Sharma, Madhuri Thakur, and Vivek Kadam. "Coal Mine Safety Monitoring and Alerting System with Smart Helmet." ITM Web of Conferences 44 (2022): 01005. http://dx.doi.org/10.1051/itmconf/20224401005.

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Traditional monitoring systems in coal mines are difficult to install, hazardous, and difficult to power. Because of the complexity of the mining environment and the wide range of operations performed in coal mines, it is vital to monitor and maintain the parameters in the background t increase the efficiency and safety of mineworkers. As a result, traditional monitoring methods cannot be relied on to ensure coal workers’ safety. This research represents a ZigBee-based wireless monitoring system using a smart helmet. The presented wireless monitoring system is capable of detecting and transmitting critical parameters in coal mines such as methane gas, high temperature, humidity, and fire. In an emergency, this monitoring system transmits distress signals. A buzzer will sound if emergency conditions are detected, and the monitored variables will be displayed on the user interface machine. Moreover, the Parameters are wirelessly transmitted to the control room, allowing people to determine the safety situation of the mine. This model is easily reprogrammable. Experiments have demonstrated the system’s reliability and stability.
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Khattar, Prerna. "A Smart Helmet for Secure Monitoring of Miner Data to Improve Safety." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 2812–18. http://dx.doi.org/10.22214/ijraset.2022.41393.

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Abstract: In recent times, mining has been a dangerous activity taking a severe toll on the lives of miners. Underground mining hazards include gas poisoning, suffocation, roof collapse, and gas explosion. This project aims to develop a smart helmet based on Zigbee wireless technology to build wireless sensor networks for real-time surveillance and monitoring hazardous gases and abnormal levels of temperature and humidity in the mine. These three parameters are continuously being detected using the gas sensor(s), temperature and humidity sensor, and if the predefined limit is crossed, a buzzer and LED will be initiated. Two infrared sensors, one inside and one on the surface of the helmet, are placed to check if the helmet is properly placed and to detect collision from falling debris, respectively. These values are continuously being transmitted to the control room for monitoring. In case of any hazardous situation, the led and buzzer are activated in the control room as well as on the miner’s helmet. The helmet is powered by the energy generated from piezoelectric sensors placed in the miner’s shoes, which work on the principle of vibration detected from the miner’s movement. The safety measures included in our project can drastically help us avoid mining accidents and thus saving invaluable lives. Keywords: Smart helmet, Zigbee Technology, Gas sensor, Temperature and Humidity sensor, Infrared Sensor, Coal mines, Safety
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P. L, Seetha. "Wireless Advanced Helmet and Accidental Free Transportation System." International Journal for Research in Applied Science and Engineering Technology 6, no. 5 (2018): 518–26. http://dx.doi.org/10.22214/ijraset.2018.5085.

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Shravya, Keesari, Yamini Mandapati, Donuru Keerthi, Kothapu Harika, and Ranjan K. Senapati. "Smart helmet for safe driving." E3S Web of Conferences 87 (2019): 01023. http://dx.doi.org/10.1051/e3sconf/20198701023.

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A smart helmet is a type of protective headgear used by the rider which makes bike driving safer than before. The main purpose of this helmet is to provide safety for the rider. This can be implemented by using advanced features like alcohol detection, accident identification, location tracking, use as a hands free device, fall detection. This makes it not only a smart helmet but also a feature of a smart bike. It is compulsory to wear the helmet, without which the ignition switch cannot turn ON. An RF Module can be used as wireless link for communication between transmitter and receiver. If the rider is drunk the ignition gets automatically locked, and sends a message to the registered number with his current location. In case of an accident it will send a message through GSM along with location with the help of GPS module. The distinctive utility of project is fall detection; if the rider falls down from the bike it sends a message.
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Dissertations / Theses on the topic "Wireless helmets"

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Артемчук, А. В., та М. В. Чередник. "Напрями розвитку та проблеми VR-технологій". Thesis, Сумський державний університет, 2018. http://essuir.sumdu.edu.ua/handle/123456789/67106.

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Віртуальна реальність (VR) - це штучний світ, створений спеціальними технічними пристроями, за допомогою яких людина може потрапити у цифровий світ. Головна відмінність віртуальної реальності - максимальний вплив на почуття людини - зір, слух, дотик.
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Funck, Jürgen Helmut [Verfasser], Clemens [Akademischer Betreuer] Gühmann, Clemens [Gutachter] Gühmann, Gerd [Gutachter] Scholl, and Reinhold [Gutachter] Orglmeister. "Synchronous data acquisition with wireless sensor networks / Jürgen Helmut Funck ; Gutachter: Clemens Gühmann, Gerd Scholl, Reinhold Orglmeister ; Betreuer: Clemens Gühmann." Berlin : Universitätsverlag der TU Berlin, 2018. http://d-nb.info/1162545992/34.

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Book chapters on the topic "Wireless helmets"

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Ma, Yuhang, and Yinfeng Fang. "Safety Helmet Wearing Recognition Based on YOLOv5." In Mobile Wireless Middleware, Operating Systems and Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98671-1_10.

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Hu, Shu-Jen, Ling-Huey Su, and Jhih-Hao Laio. "Utilizing QFD and TRIZ Techniques to Design a Helmet Combined with the Wireless Camcorder." In Proceedings of the Institute of Industrial Engineers Asian Conference 2013. Springer Singapore, 2013. http://dx.doi.org/10.1007/978-981-4451-98-7_40.

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Selvaraj, Santhi, and Umakanth N. "Providing Safety and Detecting Accidents in Bike Transport With Smart Helmets Using IoT." In Advances in Logistics, Operations, and Management Science. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8040-0.ch013.

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IoT is the network of interconnected devices or things that are embedded with sensors, software, and network connectivity. The road mishaps are also increasing day by day, due to which many deaths occur, most of them caused by the negligence of not wearing helmets, and also many deaths occur due to lack of medical attention needed by the injured person, hence the need for a protective headgear that makes bike driving safer than before. This work is implemented by considering advanced features like alcohol detection and fall detection by using alcohol and accelerometer sensors and makes not only a smart helmet but also a feature for smart bikes. RF module is a wireless device that is used to communicate between transmitter and receiver. If the rider is found drunk, the ignition switch is locked automatically, and in event of accident, the abnormal value in accelerometer is detected and message is sent to their registered number by using GSM. Thus, if a bike rider falls from bike, the message is sent automatically, and medical attention is given immediately.
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Ozsahin, Dilber Uzun, John Bush Idoko, Mohamad Hejazi, et al. "Design and implementation of wireless helmet and mechanical wheelchair." In Modern Practical Healthcare Issues in Biomedical Instrumentation. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-85413-9.00014-1.

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Conference papers on the topic "Wireless helmets"

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AL-Qutami, Tareq Aziz, and Fatin Awina Awis. "Personnel Real Time Tracking in Hazardous Areas Using Wearable Technologies and Machine Learning." In International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21426-ms.

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Abstract Real-time location information is essential in the hazardous process and construction areas for safety and emergency management, security, search and rescue, and even productivity tracking. It's also crucial during pandemics such as the COVID-19 pandemic for contact tracing to isolate those who came to the proximity of infected individuals. While global positioning systems (GPS), can address the demand for location awareness in outdoor environments, another accurate location estimation technology for indoor environments where GPS doesn't perform well is required. This paper presents the development and deployment of an end-to-end cost-effective real-time personnel location system suitable for both indoor and outdoor hazardous and safe areas. It leverages on facility wireless communication systems, wearable technologies such as smart helmets and wearable tags, and machine learning. Personnel carries the client device which collects location-related information and sends it to the localization algorithm in the cloud. When the personnel moves, the tracking dashboard shows client location in real-time. The proposed localization algorithm relies on wireless signal fingerprinting and machine learning algorithms to estimate the location. The machine learning algorithm is a mix of clustering and classification that was designed to scale well with bigger target areas and is suitable for cloud deployment. The system was tested in both office and industrial process environments using consumer-grade handphones and intrinsically safe wearable devices. It achieved an average distance error of less than 2 meters in 3D space.
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Lokeshwaran, M., S. P. Nikhit Mathew, and A. Joshuva. "Raphael—The Smart Helmet." In 2020 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET). IEEE, 2020. http://dx.doi.org/10.1109/wispnet48689.2020.9198463.

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Liu, Lei, and Benkang Chang. "The design of CY-1R night vision helmet." In Asia-Pacific Optical and Wireless Communications. SPIE, 2004. http://dx.doi.org/10.1117/12.519735.

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Watson, M. A., H. J. White, N. B. Aldridge, J. Lam, and R. Atkinson. "Cockpit to helmet optical wireless link: prototype hardware demonstration." In SPIE Europe Security + Defence, edited by Edward M. Carapezza. SPIE, 2009. http://dx.doi.org/10.1117/12.830682.

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Charlton, David W., Malcolm A. Watson, and Henry J. White. "Body-worn optical wireless link to helmet mounted display." In Security + Defence, edited by Edward M. Carapezza. SPIE, 2010. http://dx.doi.org/10.1117/12.865124.

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S., Sasirekha, Joe Louis Paul I., Swamynathan S., Y. Gokul., and P. Kirthana. "Smart Helmet with Emergency Notification System-A Prototype." In 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016). Atlantis Press, 2017. http://dx.doi.org/10.2991/icwcsn-16.2017.12.

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Qiu, Han, Zhiyuan Chen, and Fanghao Zhong. "Multifunctional Miners Helmet Design based on Wireless Sensor Network Technology." In 2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering. Atlantis Press, 2015. http://dx.doi.org/10.2991/icmmcce-15.2015.34.

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M S, Muneshwara, Anand R, Shivakumara T, Swetha M S, and Chethan A. S. "Advanced Wireless techniques to avoid accidents on roads through wearing Smart helmet." In 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2021. http://dx.doi.org/10.1109/iciccs51141.2021.9432193.

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Oh, Sechang, Prashanth Shyam Kumar, Hyeokjun Kwon, Pratyush Rai, Mouli Ramasamy, and Vijay K. Varadan. "Wireless health monitoring helmet for football players to diagnose concussion and track fatigue." In SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, edited by Vijay K. Varadan. SPIE, 2013. http://dx.doi.org/10.1117/12.2009719.

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Panja, Biswajit, Zachary Scott, and Priyanka Meharia. "Security in wireless sensor networks for health monitoring helmet with anomaly detection using power analysis and probabilistic model." In 2014 IEEE Conference on Wireless Sensors (ICWiSe). IEEE, 2014. http://dx.doi.org/10.1109/icwise.2014.7042664.

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