The higher objective of this application is to promote a safe
and more ecological driving method which encourages drivers
to be more conscious about their behavior on road.
A mathematical model is developed for predicting vehicle fuel
consumption using instantaneous engine RPM (Revolutions
per minute) and TPS (Throttle Position Sensor) through OBDII [3]. The fuel consumption varies highly with the model
variables engine RPM and TPS. It is seen that the model using
instantaneous engine RPM, TPS and (RPM, TPS) can predict
the fuel consumption quite well.
An embedded system to detect vehicle condition [4] helps
monitor the internal parameters. This information is vital to
the travellers to provide safety, security and mobility and also
improves the reliability of travel. Continuous data on
performance of vehicle and status of its internal components is
sent as information to the traveller. In this process, the vehicle
also acts as an eco-friendly vehicle as it monitors the
emissions and regulates the environment pollution. The data
required to alert the user about future errors is obtained using
OBD-II protocol. LabVIEW is usedas a platform that has
automotive diagnostic command set tool kit which helps in
building up the software required to communicate with the
vehicle’s ECU through OBD-II system. LabVIEW is a
system-design platform and development environment for a
visual programming language.
In “On-Board diagnostic system for vehicles” [5], an OBD
system consists of Arduino Board with ATMEGA
microcontroller that acts like a processing unit. The program
uses Arduino software, sensors, LCD and keypad as user
interface. The data is collected from sensors that are installed
at different parts of the vehicle to sense various vehicle results
are viewed from LCD display. ZigBee is used for wireless
data transmission. ZigBee is a new kind of short distance, low
power consumption, low cost, low rate and low complexity
wireless network technology.
An android-based application that monitors the vehicle
through OBD-II interface[6] detects accident. This application
calculates the G force. It is the measurement of the type of
acceleration that is caused by mechanical contact-forces
between object surfaces. Using G force experienced by the
passengers in case of a frontal collision and along with airbag
triggers accidents are detected and are followed by automatic
phone calls to the emergency services.
A knowledge-based framework for a driving assistance via
smartphone [7] uses OBD-II protocol to extract vehicle
information. Later the data acquired from smart-phone
embedded micro-devices and information retrieved from the
Web are properly combined. To identify and annotate relevant
contexts and events in real time Data fusion and classification
algorithms are used. Further, semantic-based matchmaking is
exploited to infer dysfunctional situations [7].