Automatic prediction of traffic in offline mode

bhal chandra ram tripathi

bhal chandra ram tripathi

Bengaluru, Karnataka

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the application will be based on the predicting the road traffic in offline internet connectivity by analyzing the stored data and performing the result synthesis. ...learn more

Project status: Concept

HPC, Artificial Intelligence

Intel Technologies
Intel CPU

Overview / Usage

Today google maps is the defacto app used for the
direction and traffic analysis. The proposed work illustrates
the solution to a problem of finding traffic between any two
points. The technique adopted in this work is predictive form
of Machine Learning and the analysis and the prediction of the
traffic is done. The use of machine learning method enables
traffic analysis in offline mode much easier and expand the
span of maps working. The traffic data is collected from users,
through API “here” and several other API’s to collect the data.
These data are used to predict the traffic when needed. The
application will behave as a normal direction provider on
Internet Connectivity but as soon as the user goes offline, the
real use of application prevails.

Methodology / Approach

Logically thinking to use the machine learning to make the application learn automatically. and use the data analysis for the deep through to the data.

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