dc.description.abstract |
The fact that most drivers these days carry their smartphones with them presents a great
opportunity to develop a new type of applications that harvest and interpret the
tremendous amount of data smartphones’ sensors collect. Smart-in-car sensing presents
smart solutions to several today’s problems faced by drivers. One of the problems
smartphones can help solve is traffic congestion. Fuel economy driving is another goal
smartphone can help drivers achieve. Combining that with a solution to traffic
congestion can contribute to low carbon dioxide emissions. A smooth and comfortable
drive is something else smartphones sensors can help the drivers achieve. Moreover,
smart-in-car sensing can prevent drowsy driving, which is a major cause of accidents.
Furthermore, context-aware data provided by smart-in-car sensing is a gold mine of
information that stakeholders can use to make better plans and to further the transition
to smart cities. The proposed android application uses smartphones’ accelerometer
sensor to detect major events the car driver encounters during his daily drive. The
application has to deal with many challenges, one of these is the fact that sensors’ data,
especially the accelerometer, produces too much noise, and to make use of the sensor’s
data there must be a way to filter out unwanted components of the data. Moreover, even
low power sensors, like the accelerometer, in the fastest mode, can put considerable
power demands on the smartphone’s battery. Interpreting sensors’ data and putting it
into context is also a great challenge. The application was able to detect road bumps,
driving behavior, and the effect of aggressive driving on the fuel consumption of the
car. Moreover, the application can detect when a car enters a traffic jam, geotagging
the location of the traffic jam, and share it with other drivers or simply upload it to the
cloud. |
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