Paper Title
Fall Detection of Riders using Inertial Sensors: A Smart Helmet
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Registration ID: IJNRD_190947
Published ID: IJNRD2304217
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Keywords
Accelerometer, Classification, Fall Detection, Feature Extraction, Feature Selection, Gyroscope, Smart Helmet
Abstract
A helmet is a protective headgear used by riders to make driving safer and avoid injuries. In this paper, a smart helmet is designed which is capable of detecting fall of riders and then transmitting a message through a global system of mobile (GSM) module along with the location of fall using global positioning system (GPS) avoiding delays to rescue. Inertial sensors, i.e., gyroscope and accelerometer sensors with a three axis sensing unit, are placed within the helmet and controlled via ARDUINO based microcontroller for fall detection. The designed helmet is used for data acquisition in 28 trials, and twenty-two statistical features are extracted from the recorded data. A subset of discriminating features are selected using the wrapper method and four different classifiers, i.e., Naïve Bayes, k-nearest neighbor, random forest, and support vector machine are applied on selected features to classify the two states i.e., fall and non-fall. It is evident from results that the Naïve Bayes classifies the fall of riders with the highest accuracy of 98.21%. The proposed methodology outperforms the existing state-of the-art fall detection techniques in terms of classification accuracy.
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How To Cite (APA)
B.KAVYA, A.V.SAI YASWANTH, M.HIMAJA, K.S.V.ABHILASH, & M.SUNEEL (April-2023). Fall Detection of Riders using Inertial Sensors: A Smart Helmet . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), c118-c122. https://ijnrd.org/papers/IJNRD2304217.pdf
Issue
Volume 8 Issue 4, April-2023
Pages : c118-c122
Other Publication Details
Paper Reg. ID: IJNRD_190947
Published Paper Id: IJNRD2304217
Research Area: Engineering
Author Type: Indian Author
Country: spsr nellore, AP, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2304217.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304217
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