Abstract:
Nowadays, monitoring road and traffic prediction
in urban area is becoming an important role in
developing countries like ours. It is the most
important part that getting and performing the
accurate traffic data in all Traffic Prediction System.
This paper introduces an approach of tracking traffic
data using the cheapest way and it was computed the
traffic data in terms of communication, computation
and energy efficient ways. Mobile devices are
becoming an important role not only for personal
contact, but also for business and environmental
sensing application. The GPS sensor of mobile device
will be mainly utilized to guess a user’s transportation
mode, then it integrates cloud environment to enhance
the limitation of mobile device, such as storage,
energy and computing power. This system includes
three main components: Client Interface, Server
process and Cloud Storage. Some tasks are carried
out on the Client. Therefore, it greatly reduces the
bottleneck situation on Server side in efficient way.
Most of tasks are executed on the Server and history
data are stored on the Cloud Storage. Firstly, the
user’s transportation mode, motorize or nonmotorized,
is analyzed on the client side using raw
GPS data, instead of submitting frequently raw data
to data center. If it is only the motorize mode, some
useful traffic data are offloaded to cloud. On the
server side, all motorize mode are not taken into
account as traffic data. In this case, the mobile data
that comes from the same location are recognized as
one proves. Later, these data are used as history data
for future prediction to perform more accurate traffic information.
