Relevant bibliographies by topics / Smart Helmet

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

Academic literature on the topic 'Smart Helmet'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Smart Helmet"

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Choi, Yosoon, and Yeanjae Kim. "Applications of Smart Helmet in Applied Sciences: A Systematic Review." Applied Sciences 11, no. 11 (May 29, 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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Lokhande, N. L. "Smart Helmet." International Journal for Research in Applied Science and Engineering Technology 7, no. 4 (April 30, 2019): 3941–45. http://dx.doi.org/10.22214/ijraset.2019.4659.

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Durgale, Sheetal. "Smart Helmet." International Journal for Research in Applied Science and Engineering Technology 7, no. 5 (May 31, 2019): 567–72. http://dx.doi.org/10.22214/ijraset.2019.5095.

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PS, Jibin. "Smart Helmet." International Journal for Research in Applied Science and Engineering Technology 7, no. 6 (June 30, 2019): 95–98. http://dx.doi.org/10.22214/ijraset.2019.6020.

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Samual, Mr Bipin. "Smart Helmet." International Journal for Research in Applied Science and Engineering Technology 6, no. 5 (May 31, 2018): 1275–79. http://dx.doi.org/10.22214/ijraset.2018.5209.

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Tiwari, Deo Raj, Akshay Kumar Sharma, Akhlaqur Rahman, Ahmar Kamran, and Ajit Agrahari. "Smart Helmet." Invertis Journal of Science & Technology 12, no. 2 (2019): 37. http://dx.doi.org/10.5958/2454-762x.2019.00008.8.

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Varshney, Abhishek. "Smart Helmet." International Journal for Research in Applied Science and Engineering Technology V, no. IV (April 27, 2017): 1027–31. http://dx.doi.org/10.22214/ijraset.2017.4185.

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Singh, Vikram. "Smart Helmet." International Journal for Research in Applied Science and Engineering Technology 6, no. 3 (March 31, 2018): 2254–58. http://dx.doi.org/10.22214/ijraset.2018.3523.

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Reddy, Nelakurthi Spoorthi. "Smart Helmet." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4075–89. http://dx.doi.org/10.22214/ijraset.2021.35851.

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Road accidents are increasing day by day because the riders are not using the helmet and due to consumption of alcohol. In today's world, huge numbers of people are dying on road accidents. By using smart helmet, the accidents can be detected. The main target of the project is designing a smart helmet for accident avoidance and alcohol detection. The features of the Smart Helmet are wearing helmet, detection of alcohol, detection of accident. If the person is not wearing helmet the bike will not start and it displays on the LCD. The alcohol sensor recognizes the alcoholic substance in the rider's breath. If the person is drunk then alcohol sensor detects it and displays on the LCD and the bike will not start. If there is no detection of alcohol then the bike starts. If there is no sign of alcoholic substance present and helmet is used, only then the bike will start. The bike will not start if any of the two conditions is violated. If an accident is occurred then it is detected by Vibration sensor and alarm is activated. If the person is in conscious state, then the person can off the alarm and no message is sent to the saved numbers. If the person is in unconscious state, then message will be sent to the saved numbers in GSM module and sends the location to them by GPS. With the use of Smart Helmet, accident rate can be reduced.
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Sobhana, S., S. R. Sowmeeya, M. Srinathji, and S. Tamilselvan. "Smart Helmet." IOP Conference Series: Materials Science and Engineering 1084, no. 1 (March 1, 2021): 012116. http://dx.doi.org/10.1088/1757-899x/1084/1/012116.

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Dissertations / Theses on the topic "Smart Helmet"

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Llull, Patrick Ryan, Louie Benitez, Cedric Bosch, Stephen Nelson, Garrett Weaver, and Trevor West. "Jockey Smart Helmet." Thesis, The University of Arizona, 2012. http://hdl.handle.net/10150/244431.

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The horseracing industry currently lacks media attention. Studies have indicated the sport’s viewing and gambling declination over the decades. While popular televised sports such as football and baseball maintain a modernized entertainment culture through high-definition wireless streaming, horseracing remains in the 'binocular era'. An idea is introduced and a solution is analyzed to establish a foothold for horseracing in contemporary entertainment and inspire a developing fan base. EquiSight LLC desires wireless telemetry within the form factor of a jockey's helmet to meet these ends. The system devised must function while satisfying safety regulations. Individual component decisions are justified in addition to safety and quality tests. Current technology restricts bandwidth and data transfer rate. Standard-and high-definition possibilities and implications are discussed. Analog and digital transmission systems are evaluated and a preference justification is developed. A reliable power source and integration technique are chosen. Environmental, space, and range constraints are considered. Two-way audio communication between the jockey and trainer is described. In summary, a compact solution for EquiSight LLC is presented and its design choices are reviewed. The proposed system, implemented within a $3000 budget, will attract new fans, reignite interest, and provide a fairness and/or outcome judging tool.
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Altinsoy, Sinan. "Zero-Power Fall Detection System for Smart Helmets." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21618/.

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The widespread use of vehicles has led to an increase in traffic accidents. In these accidents, motorcyclists are exposed to more risks because they are more vulnerable than car drivers. With the development of technology, manufacturers have increased their work on vehicle security systems. Advancements in these studies which are being applied in daily life resulted in a reduction of risks in accidents. In this thesis, Zero-Power Fall Detection System is developed for smart helmets, which is a safety system for motorcycles. Since the lifetime of electronic devices has become one of the most important features of today, the aim of this study is to design a self-sustainable fall detection system that consumes as low power as possible. First, the system is designed with Piezoelectric Wake-up Circuits, a microcontroller unit with bluetooth low energy communication and a self-sustainable battery management system with high efficiency power recovery. Then, a fall detection algorithm is designed to send a message to a smartphone, tablet or etc. through bluetooth low energy connection when hazardous situations are detected. Based on this algorithm, the software of the system is prepared. Finally, field tests have been carried out and according to the results, it has been shown that the fall detection system developed is functional and has a very low power consumption.
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Ehrenhofer, Adrian, Alice Mieting, Sascha Pfeil, Johannes Mersch, Chokri Cherif, Gerald Gerlach, and Thomas Wallmersperger. "An automatically rainproofing bike helmet through light-sensitive hydrogel meshes: Design, modeling and experiments." SPIE, 2020. https://tud.qucosa.de/id/qucosa%3A74218.

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For everyday cycling, one needs to carry rainproof clothing just for the case of unexpected downpours. In the present research, we present a concept for a helmet which is automatically rainproof when the rain starts. When the sun comes out, the helmet is breathable again even before it completely dries up. This functionality is provided by active hydrogel meshes. Hydrogel meshes offer great advantages due to their ability to change the aperture size with swelling and deswelling. In our current work, we present the design and modeling steps for hydrogel-layered active meshes which use (i) swelling and deswelling in hydrated state and (ii) swelling starting from the dry state. The main goal is to close the air openings of a bicycle helmet when rain starts as an automatic rainproofing. This can be achieved through the swelling of the hydrogel pNiPAAM-co-chlorophyllin in the meshes, which leads to closing when hydrated. At the same time, the light-sensitive behavior leads to opening of the apertures under direct sun exposure, i.e. when the sun appears again after the rain. We present the steps of modeling and design using the Normalized Extended Temperature-Expansion-Model (NETEM) to perform simulations in Abaqus. The model is capable of describing both the swelling of the hydrogel under light stimulus and the volume change due to hydration. It is based on the analogy between free swelling and thermal expansion and defined for nonlinear displacements. We also discuss the fabrication process of hydrogel-layered fibers and challenges in their application and simulation. As a proof of concept for hydrogel-layered meshes, we show preliminary experimental results of a poly(acrylamide)/poly(2-acrylamido-2-methyl-1-propanesulfonic acid) (PAAm/PAMPS) hydrogel with semi-interpenetrated network (SIPN) structure and its swelling capacities on a mesh. Starting from the active hydrogel meshes as presented in the current work, the next step can be smart textiles that harness the power of hydrogels: the adaptation to combinations of stimuli - like humidity, temperature and brightness - that define environments.
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Huang, Guan-Lin, and 黃冠霖. "Design of Android Interface for GPS Navigation Map on Smart Helmet." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/d4rnj2.

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碩士
國立臺北科技大學
電子工程系研究所
105
In todays society, the navigation system has been popularized of the public, and many cars are equipped with GPS navigation system to provide the driver with accurate navigation information and save time, but the locomotive doesn’t install the system yet. At present, Taiwan roads are complicated, people often waste time on search for destination because they are not familiar with the road. Therefore, this paper proposes a smart map navigation helmet, mainly designed for locomotive ethnic groups, which is characterized by real-time GPS positioning, and projection in the goggles above, so that drivers can get the latest navigation information , Shorten travel time and provide convenience and entertainment. Helmets embedded Smart Glass Device and equipped with Bluetooth module to receive mobile phone information, WIFI module display HTML and load Google Map, request Google APIs Server navigation information, GPS module positioning, touch panel module, select APP and set the Smart Glass Device system parameters, micro-projector module projection screen to the helmet goggles, the device miniaturized circuit board design can move into the helmets. Mobile phone side can be driven according to the needs of different navigation methods to make helmet end display. The device also uses the highest market share of the highest Android operating system and simple man-machine interface design, so that is easier for beginner. Improve the locomotive population down the head of the mobile phone situation, reduce the swing action, reduce the risk of locomotive driving and shorten the driving time.
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Her, Yi-Shyang, and 赫弋翔. "Design of Head-Up Speed Display for Motorbike Helmet Based on Smart Phone GPS." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/w4s3ju.

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碩士
國立臺北科技大學
電腦與通訊研究所
101
This thesis set up a head-up display for motobike helmet. Today, haed-up display has been used normally in car. But never see any store sell head-up display for motocyclists in Taiwan. Motocyclist have to bow the head when heshe want to see the speed information, because the dashboard is between motobike’s handlebars. So ridding motorbike is more dangerous than driving car. Also government lifts the ban against riding on the highway for huge heavy motorbikes (above 250cc). As a result of head-up display have huge potential for motorbike market. In this thesis, head-up display device is made of microcontroller, Bluetooth module and 7-segement display. Device get speed and direction data from smart phone GPS application through Bluetooth, that can reduce down the cost of product. In the future, we can use some soft and transparent display to improve the functionality and increase the display space . PIC16 series is 8 bit microcontroller, only have 35 assembly language. Use this microcontroller receive the speed and direction data from smart phone through Bluetooth module. In the end, we test whole system in open space and discuess factors which effect the accuracy of GPS speedometer.
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Li, Ping. "Safety analysis using a Smart Safety Helmet embedded with IMU and EEG sensors applied in industrial facility." Thèse, 2015. http://constellation.uqac.ca/3315/1/Li_uqac_0862N_10126.pdf.

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Some mental states, such as fatigue, or sleepiness, are known to increase the potential of accidents in industry, and thus could decrease productivity, even increase cost for healthcare. The highest rate of industrial accidents is usually found among shift workers due to fatigue or extended work hours. When using machine tool or interacting with robotic system, the risk of injury increases due to disturbance, lapse in concentration, vigilance decline, and neglect of the risk during prolonged use. Usually, to guarantee safety of worker, the conventional means is to stop the machine when human presence is detected in the safeguarding area of machine tool or robot workspace. The popular human detection technologies exploit laser scanner, camera (or motion tracker), infrared sensor, open-door sensor, static pressure sensitive floor as described in CSA Z434 standard. Of course, in the field of robotic, human and robot are not allowed to work together in the same workspace. However, new industrial needs lead research to develop flexible and reactive chain production for enabling small quantity production or fast modification in product characteristics. Consequently, more efficient human-machine or human-robot collaboration under a safety condition could improve this flexibility. Our research project aims at detecting and analyzing human safety in industry in order to protect workers. Comparing to the conventional human protection methods, our research exploits Artificial Intelligence approach to track and monitor human head motion and mental state using an instrumented safety helmet, labelled as Smart Safety Helmet (SSH) in the following. The contribution of this thesis consists in the design of data fusion algorithm for the recognition of head motion and mental state, which can be used to analyze the potential risky states of workers. A Smart Safety Helmet embedded with Inertial Measurement Unit (IMU) and EEG sensors will be used to detect and decode the human’s mental state and intention. The acquired information will be used to estimate the accident risk level in order to stop machine and then prevent accident or injury. In human-robot interaction (HRI) paradigm, the human’s intention could be used to predict the worker trajectory in order to control the robot moving trajectory and then to avoid fatal collision. Certains états mentaux, comme la fatigue ou la somnolence, sont connus pour augmenter le potentiel d'accidents dans l'industrie, et pourrait donc réduire la productivité, même augmenter les coûts des soins de santé. Le taux le plus élevé d'accidents au travail est habituellement trouvé parmi les travailleurs en rotation (travail posté) dues à la fatigue ou les heures de travail prolongées. Lors de l'utilisation d’une machine-outil ou lors d’une interaction avec un système robotique, le risque de lésion peut augmenter dû à une perturbation, un manque de concentration, une baisse de vigilance et la négligence du travailleur face au risque présent lors d'une utilisation prolongée (accoutumance au risque). Habituellement, pour garantir la sécurité des travailleurs, des moyens classiques sont l'arrêt complet de la machine lorsque la présence humaine est détectée dans une zone non sécuritaire, par exemple dans l’espace de travail d’un robot. Les technologies industrielles communes de détection humaine exploitent le scanner au laser, la caméra (par la capture de mouvement), le capteur infrarouge, l’interrupteur de porte ouverte, le tapis de capture de la pression statique ; tous ces capteurs sont décrits dans la norme CSA Z434. Jusqu’à tout récemment, dans le domaine de la robotique industrielle, les humains et les robots n’étaient pas autorisés à travailler ensemble dans le même espace. Toutefois, des besoins industriels émergents ont dirigé les recherches pour développer une production flexible et réactive pour favoriser la production de petites quantités ou modifier rapidement des caractéristiques du produit. Par conséquent, une collaboration plus efficace entre l'humain et le robot ou, de manière plus générale entre l'humain et la machine, sous des contraintes de sécurité, pourrait améliorer cette flexibilité et cette réactivité. Notre projet de recherche vise à détecter et à analyser la sécurité humaine dans l'industrie afin de protéger les travailleurs. En comparant les méthodes classiques de protection humaine, notre approche exploite l'intelligence artificielle pour identifier les mouvements de la tête et identifier l'état mental en utilisant un casque de sécurité instrumenté, nommé le Smart Safety Helmet (SSH) dans ce qui suit. La contribution de ce mémoire réside dans la conception de la fusion des données provenant de la reconnaissance de mouvement de la tête et de l'état mental, qui peut être utilisée pour analyser le potentiel de risque encouru par un travailleur. Dans le SSH, une unité de mesure inertielle (IMU) et capteurs EEG ont été intégrés. Ces deux capteurs seront utilisés pour détecter l'état mental de l’humain et décoder son intention. Les informations recueillies seront utilisées pour estimer le risque d'accidents afin d'arrêter la machine et d'empêcher un accident. Dans le paradigme de l’interaction humain-robot, l'intention de l'humain pourrait être utilisée modifier le comportement du robot (réduire sa rigidité ou modifier sa trajectoire).
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Cicoszki, Tatiane. "Desenvolvimento de projeto de um sistema de ventilação automatizado para capacete de bicicleta Smart Helmet IPB-UTFPR." Master's thesis, 2021. http://hdl.handle.net/10198/23874.

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Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do Paraná
Os capacetes de bicicleta são a forma mais eficiente de reduzir os danos na cabeça causados por acidentes envolvendo ciclistas. Entretanto, muitos usuários evitam usá-los por considerarem, entre outros motivos, o equipamento desconfortável termicamente. As camadas de proteção dificultam a perda de calor em ambientes quentes e as aberturas de ventilação fazem com que a perda de calor seja exagerada em condições de baixa temperatura. A presente dissertação consiste em uma proposta para solucionar essa barreira de uso e colaborar para que estes equipamentos se tornem versáteis e confortáveis em diferentes situações. Um mecanismo de palhetas rotativas foi desenvolvido para ser impresso através de fabrico aditivo (prototipagem rápida) e atuar juntamente com um sistema eletrônico, controlado por um microcontrolador ESP32. Este é responsável por identificar a temperatura sob o capacete, através da utilização de um sensor termistor, e acionar um servomotor, alterando o posicionamento das palhetas, liberando ou restringindo a entrada de ar. Consiste em um trabalho essencialmente teórico, tendo em vista que a ocorrência da pandemia causada pelo Covid-19 impediu a realização do trabalho experimental, que permitiria validar o projeto. Contudo, conclui-se que o mecanismo proposto parece exequível e aplicável em capacetes já existentes ou adequáveis a novos modelos.
Bicycle helmets are the most efficient way to reduce head damage caused by accidents involving cyclists. However, many users avoid using them because they consider, among other reasons, the equipment thermally uncomfortable. The protective layers make heat loss difficult in hot environments and the ventilation openings cause heat loss to be exaggerated in low temperature conditions. This dissertation consists of a proposal to solve this barrier of use and collaborate so that this equipment becomes versatile and comfortable in different situations. A rotary vane mechanism was developed to be printed through additive manufacturing (rapid prototyping) and to act together with an electronic system, controlled by an ESP32 microcontroller. This is responsible for identifying the temperature under the helmet, using a thermistor sensor, and activating a servomotor, changing the position of the vanes, releasing or restricting the air intake. It consists of essentially theoretical work, considering that the occurrence of the pandemic caused by Covid-19 prevented the experimental work, which would allow the project to be validated. However, it is concluded that the proposed mechanism seems feasible and applicable to existing helmets or suitable for new models.
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Books on the topic "Smart Helmet"

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Get head smart: How to choose a bicycle helmet. Salem, Or: Oregon Dept. of Transportation, Bicycle Safety Program, 1999.

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United States. National Highway Traffic Safety Administration, ed. Be head smart. [Washington, DC: National Highway Traffic Safety Administration, 1994.

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United States. National Highway Traffic Safety Administration, ed. Be head smart. [Washington, DC: National Highway Traffic Safety Administration, 1998.

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Workbook for Heller/Veach's Clinical Medical Assisting: A Professional, Field Smart Approach to the Workplace. Delmar Cengage Learning, 2016.

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LLC, Motosafer. Motorcycle Gear: The Ultimate Guide to the Safest Helmets, Jackets, Pants, Gloves, Boots, Airbags, & Accessories. Make Smart Buying Decisions, Avoid Life-Threatening Bike Accidents & Ride Confidently. Independently Published, 2019.

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Hegland, Frode, ed. The Future of Text. Future Text Publishing, 2020. http://dx.doi.org/10.48197/fot2020a.

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This book is the first anthology of perspectives on the future of text, one of our most important mediums for thinking and communicating, with a Foreword by the co-inventor of the Internet, Vint. Cerf and a Postscript by the founder of the modern Library of Alexandria, Ismail Serageldin. In a time with astounding developments in computer special effects in movies and the emergence of powerful AI, text has developed little beyond spellcheck and blue links. In this work we look at myriads of perspectives to inspire a rich future of text through contributions from academia, the arts, business and technology. We hope you will be as inspired as we are as to the potential power of text truly unleashed. Contributions by Adam Cheyer • Adam Kampff • Alan Kay • Alessio Antonini • Alex Holcombe • Amaranth Borsuk • Amira Hanafi • Amos Paul Kennedy Jr. • Anastasia Salter • Andy Matuschak & Michael Nielsen • Ann Bessemans & María Pérez Mena • Andries Van Dam • Anne-Laure Le Cunff • Anthon Botha • Azlen Ezla • Barbara Beeton • Belinda Barnet • Ben Shneiderman • Bernard Vatant • Bob Frankston • Bob Horn • Bob Stein • Catherine C. Marshall • Charles Bernstein • Chris Gebhardt • Chris Messina • Christian Bök • Christopher Gutteridge • Claus Atzenbeck • Daniel Russel • Danila Medvedev • Danny Snelson • Daveed Benjamin • Dave King • Dave Winer • David De Roure • David Jablonowski • David Johnson • David Lebow • David M. Durant • David Millard • David Owen Norris • David Price • David Weinberger • Dene Grigar • Denise Schmandt-Besserat • Derek Beaulieu • Doc Searls • Don Norman • Douglas Crockford • Duke Crawford • Ed Leahy • Elaine Treharne • Élika Ortega • Esther Dyson • Esther Wojcicki • Ewan Clayton • Fiona Ross • Fred Benenson & Tyler Shoemaker • Galfromdownunder, aka Lynette Chiang • Garrett Stewart • Gyuri Lajos • Harold Thimbleby • Howard Oakley • Howard Rheingold • Ian Cooke • Iian Neil • Jack Park • Jakob Voß • James Baker • James O’Sullivan • Jamie Blustein • Jane Yellowlees Douglas • Jay David Bolter • Jeremy Helm • Jesse Grosjean • Jessica Rubart • Joe Corneli • Joel Swanson • Johanna Drucker • Johannah Rodgers • John Armstrong • John Cayle • John-Paul Davidson • Joris J. van Zundert • Judy Malloy • Kari Kraus & Matthew Kirschenbaum • Katie Baynes • Keith Houston • Keith Martin • Kenny Hemphill • Ken Perlin • Leigh Nash • Leslie Carr • Lesia Tkacz • Leslie Lamport • Livia Polanyi • Lori Emerson • Luc Beaudoin & Daniel Jomphe • Lynette Chiang • Manuela González • Marc-Antoine Parent • Marc Canter • Mark Anderson • Mark Baker • Mark Bernstein • Martin Kemp • Martin Tiefenthaler • Maryanne Wolf • Matt Mullenweg • Michael Joyce • Mike Zender • Naomi S. Baron • Nasser Hussain • Neil Jefferies • Niels Ole Finnemann • Nick Montfort • Panda Mery • Patrick Lichty • Paul Smart • Peter Cho • Peter Flynn • Peter Jenson & Melissa Morocco • Peter J. Wasilko • Phil Gooch • Pip Willcox • Rafael Nepô • Raine Revere • Richard A. Carter • Richard Price • Richard Saul Wurman • Rollo Carpenter • Sage Jenson & Kit Kuksenok • Shane Gibson • Simon J. Buckingham Shum • Sam Brooker • Sarah Walton • Scott Rettberg • Sofie Beier • Sonja Knecht • Stephan Kreutzer • Stephanie Strickland • Stephen Lekson • Stevan Harnad • Steve Newcomb • Stuart Moulthrop • Ted Nelson • Teodora Petkova • Tiago Forte • Timothy Donaldson • Tim Ingold • Timur Schukin & Irina Antonova • Todd A. Carpenter • Tom Butler-Bowdon • Tom Standage • Tor Nørretranders • Valentina Moressa • Ward Cunningham • Dame Wendy Hall • Zuzana Husárová. Student Competition Winner Niko A. Grupen, and competition runner ups Catherine Brislane, Corrie Kim, Mesut Yilmaz, Elizabeth Train-Brown, Thomas John Moore, Zakaria Aden, Yahye Aden, Ibrahim Yahie, Arushi Jain, Shuby Deshpande, Aishwarya Mudaliar, Finbarr Condon-English, Charlotte Gray, Aditeya Das, Wesley Finck, Jordan Morrison, Duncan Reid, Emma Brodey, Gage Nott, Aditeya Das and Kamil Przespolewski. Edited by Frode Hegland.
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Book chapters on the topic "Smart Helmet"

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Theresa, W. Gracy, and A. Gayathri. "Smart Active Helmet." In EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing, 393–400. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19562-5_40.

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Sales, David, Paula Prata, and Paulo Fazendeiro. "Smart Helmet: An Experimental Helmet Security Add-On." In Lecture Notes in Networks and Systems, 1236–50. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80126-7_86.

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Rajathi, N., N. Suganthi, and Sourabh Modi. "Smart Helmet for Safety Driving." In Information and Communication Technology for Intelligent Systems, 407–16. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1747-7_39.

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Muni Mohith Reddy, K., D. Venkata Krishna Rohith, C. Akash Reddy, and I. Mamatha. "Smart Helmet using Advanced Technology." In Information and Communication Technology for Intelligent Systems, 479–88. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7078-0_46.

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Bhuvaneswary, N., K. Hima Bindu, M. Vasundhara, J. Chaithanya, and M. Venkatabhanu. "IoT-Based Smart Helmet for Riders." In Expert Clouds and Applications, 153–67. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2126-0_14.

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Kagalkar, Ramesh, and Basavaraj Hunshal. "A Smart and Secure Helmet for Safe Riding." In Techno-Societal 2020, 703–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69921-5_70.

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Agrahari, Ashutosh, and Dhananjay Singh. "Smart City Transportation Technologies: Automatic No-Helmet Penalizing System." In Blockchain Technologies, 115–32. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2205-5_6.

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Magno, Michele, Angelo D’Aloia, Tommaso Polonelli, Lorenzo Spadaro, and Luca Benini. "SHelmet: An Intelligent Self-sustaining Multi Sensors Smart Helmet for Bikers." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 55–67. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61563-9_5.

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Indupuru, Yogya, K. Venkatasubramanian, and V. Umamaheswari. "Design and Implementation of Smart Helmet Using Low Power MSP430 Platform." In Lecture Notes in Electrical Engineering, 211–23. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8575-8_22.

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Dhulavvagol, Praveen M., Ranjitha Shet, Prateeksha Nashipudi, Anand S. Meti, and Renuka Ganiger. "Smart Helmet with Cloud GPS GSM Technology for Accident and Alcohol Detection." In Communications in Computer and Information Science, 346–57. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-9059-2_31.

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Conference papers on the topic "Smart Helmet"

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Nataraja, N., K. S. Mamatha, Keshavamurthy, and Shivashankar. "SMART HELMET." In 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2018. http://dx.doi.org/10.1109/rteict42901.2018.9012338.

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Kanetkar, Sarika, Ankit Rathore, Krati Maheshwari, Prasanna Dubey, and Ankit Saxena. "Smart Helmet Wiper." In 2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS). IEEE, 2020. http://dx.doi.org/10.1109/sceecs48394.2020.40.

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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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Suman, Aakriti, Abhigya Parashar, Annada Shukla, and K. R. Shobha. "Aagaahi - A Smart Helmet." In 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). IEEE, 2020. http://dx.doi.org/10.1109/conecct50063.2020.9198395.

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Gudavalli, Durga K. Prasad, Bh Sudha Rani, and C. Vidya Sagar. "Helmet operated smart E-bike." In 2017 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS). IEEE, 2017. http://dx.doi.org/10.1109/itcosp.2017.8303138.

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Hottner, Lena, Elke Bachlmair, Mario Zeppetzauer, Christian Wirth, and Alois Ferscha. "Design of a smart helmet." In IoT '17: 7th International Conference on the Internet of Things. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3131542.3140275.

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Vashisth, Rashmi, Sanchit Gupta, Aditya Jain, Sarthak Gupta, Sahil, and Prashant Rana. "Implementation and analysis of smart helmet." In 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC). IEEE, 2017. http://dx.doi.org/10.1109/ispcc.2017.8269660.

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Praveena, M. D. Anto, V. Srinath, D. V. Suresh Kumar Reddy, A. Christy, and L. Suji Helen. "Smart safety helmet for underground workers." In Third International Conference on Material Science, Smart Structures and Applications: (ICMSS 2020). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0039788.

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Mohd Rasli, Mohd Khairul Afiq, Nina Korlina Madzhi, and Juliana Johari. "Smart helmet with sensors for accident prevention." In 2013 International Conference on Electrical, Electronics and System Engineering (ICEESE). IEEE, 2013. http://dx.doi.org/10.1109/iceese.2013.6895036.

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Jayasree, V., and M. Nivetha Kumari. "IOT Based Smart Helmet for Construction Workers." In 2020 7th International Conference on Smart Structures and Systems (ICSSS). IEEE, 2020. http://dx.doi.org/10.1109/icsss49621.2020.9202138.

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You might also be interested in the extended bibliographies on the topic 'Smart Helmet' for particular source types:
Journal articles
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