TY - GEN
T1 - Smart-steering
T2 - 2020 IEEE International Conference on Consumer Electronics, ICCE 2020
AU - Rachakonda, Laavanya
AU - Mohanty, Saraju P.
AU - Kougianos, Elias
AU - Sayeed, Md Abu
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - Accidents on road are severe unavoidable incidents that have been exponentially increasing every year in the United States. Statistics show that among the total accidents, 40% are due to driving intoxicated or under influence. With the growth in science and technology, robust solutions with improved, reasonable, feasible mechanisms should be proposed. Smart-Steering strives to solve this issue with a scope of reduction in the increasing rate of road accidents. This proposes a smart 'thing' which can convert the regular steering to smart steering with the help of the Internet of things. This device works with the touch of the human driver, collects and analyses the physiological data of the person and performs the analysis in a microcontroller. With the help of the analyzed data, the decision of sobriety of the human is made and sent to the car's infotainment as a notification. This data is also sent to the cloud server for storing purposes. The blood alcohol prediction is made with an exact level of the concentration present in the human body with an accuracy of approximately 93%.
AB - Accidents on road are severe unavoidable incidents that have been exponentially increasing every year in the United States. Statistics show that among the total accidents, 40% are due to driving intoxicated or under influence. With the growth in science and technology, robust solutions with improved, reasonable, feasible mechanisms should be proposed. Smart-Steering strives to solve this issue with a scope of reduction in the increasing rate of road accidents. This proposes a smart 'thing' which can convert the regular steering to smart steering with the help of the Internet of things. This device works with the touch of the human driver, collects and analyses the physiological data of the person and performs the analysis in a microcontroller. With the help of the analyzed data, the decision of sobriety of the human is made and sent to the car's infotainment as a notification. This data is also sent to the cloud server for storing purposes. The blood alcohol prediction is made with an exact level of the concentration present in the human body with an accuracy of approximately 93%.
KW - Alcohol Level Detection
KW - Blood Alcohol Concentration (BAC)
KW - Driving Under Influence (DUI)
KW - Driving While Intoxicated or Impaired (DWI)
KW - Internet of Things (IoT)
KW - Smart Cars
KW - Smart Healthcare
UR - http://www.scopus.com/inward/record.url?scp=85082603719&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85082603719&partnerID=8YFLogxK
U2 - 10.1109/ICCE46568.2020.9043045
DO - 10.1109/ICCE46568.2020.9043045
M3 - Conference contribution
AN - SCOPUS:85082603719
T3 - Digest of Technical Papers - IEEE International Conference on Consumer Electronics
BT - 2020 IEEE International Conference on Consumer Electronics, ICCE 2020
Y2 - 4 January 2020 through 6 January 2020
ER -