TY - GEN
T1 - Utilizing VIN for improved vehicular sensing
AU - Ali, Najah Abu
AU - Abuelkhair, Mervat
AU - Bouktif, Salah
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/12
Y1 - 2016/9/12
N2 - The wealth of sensor data generated by advanced vehicular sensors that are fitted in new, connected vehicles enables new applications for driver behavior, road health monitoring, and incident reporting. However, standard access mechanisms to the data restricts the services and insights that can be provided by vehicular applications. For those applications to have full access to all of the vehicular sensory data, custom hardware fitted with proprietary automaker software is needed to process raw sensor values. This limits rapid deployment at scale because of the time and costs needed for mass development across proprietary platforms. In this paper, we propose a system to provide access to the raw sensory data using the vehicle's identification number in order to retrieve the vehicles sensors identification numbers, their description, and their related software libraries that house the data processing algorithms specific to the vehicle's make and model. Smartphones can collect raw sensory data through the vehicle's CAN-Bus interface, and use those software libraries to transform raw data into standard formats that can be used by vehicular applications. This way, many applications can be developed without having to worry about customization of hardware to process the data produced by each automaker's sensor platforms.
AB - The wealth of sensor data generated by advanced vehicular sensors that are fitted in new, connected vehicles enables new applications for driver behavior, road health monitoring, and incident reporting. However, standard access mechanisms to the data restricts the services and insights that can be provided by vehicular applications. For those applications to have full access to all of the vehicular sensory data, custom hardware fitted with proprietary automaker software is needed to process raw sensor values. This limits rapid deployment at scale because of the time and costs needed for mass development across proprietary platforms. In this paper, we propose a system to provide access to the raw sensory data using the vehicle's identification number in order to retrieve the vehicles sensors identification numbers, their description, and their related software libraries that house the data processing algorithms specific to the vehicle's make and model. Smartphones can collect raw sensory data through the vehicle's CAN-Bus interface, and use those software libraries to transform raw data into standard formats that can be used by vehicular applications. This way, many applications can be developed without having to worry about customization of hardware to process the data produced by each automaker's sensor platforms.
KW - CAN-Bus
KW - OBDII
KW - VIN
KW - vehicular sensing
UR - http://www.scopus.com/inward/record.url?scp=84989829465&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84989829465&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2016.7564813
DO - 10.1109/WCNC.2016.7564813
M3 - Conference contribution
AN - SCOPUS:84989829465
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
Y2 - 3 April 2016 through 7 April 2016
ER -