TY - CHAP
T1 - Recognizing driving behaviour using smartphones
AU - Vavouranakis, Prokopis
AU - Panagiotakis, Spyros
AU - Mastorakis, George
AU - Mavromoustakis, Constandinos X.
AU - Batalla, Jordi Mongay
PY - 2017
Y1 - 2017
N2 - In this chapter at first we will present our methodology for recognizing driving patterns using smartphones, and then we will present in detail the android-based application we have developed to this end, which can monitor driving behavior. The latter can be achieved either using data only from the accelerometer sensor or using a sensor fusion method, which combines data from the accelerometer, the gyroscope and the magnetometer. We can recognize events like hard acceleration, safe acceleration, sharp left turn, safe right turn, sharp left lane change, etc. The application to improve the driving behavior of the driver, displays some hint messages to him after each bad-driving event. All the data from the trips (e.g., driving events that take place during a trip), are stored in a database and the driver has the opportunity to review and analyze them whenever he wants. We believe that organizing drivers in some form of a social network and involving them in a game-like procedure for promoting and rewarding the best driver among them, can motivate drivers to more secure driving customs.
AB - In this chapter at first we will present our methodology for recognizing driving patterns using smartphones, and then we will present in detail the android-based application we have developed to this end, which can monitor driving behavior. The latter can be achieved either using data only from the accelerometer sensor or using a sensor fusion method, which combines data from the accelerometer, the gyroscope and the magnetometer. We can recognize events like hard acceleration, safe acceleration, sharp left turn, safe right turn, sharp left lane change, etc. The application to improve the driving behavior of the driver, displays some hint messages to him after each bad-driving event. All the data from the trips (e.g., driving events that take place during a trip), are stored in a database and the driver has the opportunity to review and analyze them whenever he wants. We believe that organizing drivers in some form of a social network and involving them in a game-like procedure for promoting and rewarding the best driver among them, can motivate drivers to more secure driving customs.
KW - Accelerometer
KW - Android
KW - Driving behaviour
KW - Sensor fusion
KW - Smartphone
UR - http://www.scopus.com/inward/record.url?scp=85027268320&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-50758-3_11
DO - 10.1007/978-3-319-50758-3_11
M3 - Chapter
AN - SCOPUS:85027268320
T3 - Internet of Things
SP - 269
EP - 299
BT - Internet of Things
PB - Springer International Publishing
ER -