Download PDFOpen PDF in browser

Traffic Density Monitoring Using Tensorflow

EasyChair Preprint no. 10596

8 pagesDate: July 19, 2023


The rapid growth of urban areas and the increasing number of vehicles on the roads have led to significant challenges in traffic management and monitoring. This research proposes an intelligent traffic monitoring system that utilizes deep learning techniques to analyze video input and extract valuable information about different types of vehicles present in the traffic video input. This system employs TensorFlow, Convolution Neural Network (CNN) for object detection and classification, enabling accurate identification of cars, buses, and trucks. The detected objects are then tracked across frames to provide real-time information about their movement and behavior, hence dynamic management of waiting time can be achieved.

Keyphrases: Classification, CNN, deep learning, Intelligent traffic monitoring, object detection, TensorFlow, traffic patterns, Web-based Visualisation

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Akshantula Neha and M Raghavi and M Madhurashree and M M Ranjitha and V K Annapurna},
  title = {Traffic Density Monitoring Using Tensorflow},
  howpublished = {EasyChair Preprint no. 10596},

  year = {EasyChair, 2023}}
Download PDFOpen PDF in browser