Authors :
Delna T D; Dhanya P Pauly; Dona Johnson; Jesta Jose
Volume/Issue :
Volume 5 - 2020, Issue 7 - July
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/3hknqg5
DOI :
10.38124/IJISRT20JUL828
Abstract :
In the current smart city background, people
are facing a lot of accidents at the major traffic points of
the business towns due to growing population and
vehicles growth in smart and metropolitan cities.In this
method we consider the auto taxies as well as the public
transport. We know that due to the overload in the
vehicles the accidents are increasing day by day so using
this method the number of accidents be able to be
avoided or reduced. This system is introducing the deep
learning approach to find the overload in vehicles. We
are considering the luggage that is taken along with the
passenger and an average weight is given for the load.
Then it is combined with the number of passenger and
system will predict whether the vehicle is overload or
not. Mainly because of using deep learning concepts we
can increase the speed of the process and the efficiency.
The system will analyse the number of passengers using
real time videos using camera and system detect and
compare with the overloading conditions to
avoidaccidents.
In the current smart city background, people
are facing a lot of accidents at the major traffic points of
the business towns due to growing population and
vehicles growth in smart and metropolitan cities.In this
method we consider the auto taxies as well as the public
transport. We know that due to the overload in the
vehicles the accidents are increasing day by day so using
this method the number of accidents be able to be
avoided or reduced. This system is introducing the deep
learning approach to find the overload in vehicles. We
are considering the luggage that is taken along with the
passenger and an average weight is given for the load.
Then it is combined with the number of passenger and
system will predict whether the vehicle is overload or
not. Mainly because of using deep learning concepts we
can increase the speed of the process and the efficiency.
The system will analyse the number of passengers using
real time videos using camera and system detect and
compare with the overloading conditions to
avoidaccidents.