Vehicle Tagging using Deep Learning

Our goal is to perform real-time deep learning based object detection at security cameras, using a small, low-power setup made up of a Raspberry Pi and an Intel Movidius NCS.

Project Title

Vehicle Tagging using Deep Learning

Project Area of Specialization

Artificial Intelligence

Project Summary

Our goal is to perform real-time deep learning based object detection at security cameras, using a small, low-power setup made up of a Raspberry Pi and an Intel Movidius NCS.

Project Objectives

Features our solution will provide:

? Fully independent nodes/no single point of failure

? Autonomous vehicle recognition/tracking

? Central database only for synchronization hence

  low bandwidth requirement

Project Implementation Method

Our system will use a Raspberry pi along with an Intel Movidius NCS to perform real time analysis on video being fed to it via a camera. The system will also be connected online to enable communication between different nodes.

Benefits of the Project

Traffic surveillance is becoming an increasingly complex task due to the explosive growth in the number of vehicles on roads. It is no longer possible for humans alone to effectively manage such systems. We want to use deep learning and computer vision concepts to automate traffic surveillance.

Technical Details of Final Deliverable

The final deliverable will be a Raspberry pi/Intel Movidius combo connected to a camera. This device will be able to perform its tasks at the edge with minimal human intervention.

Final Deliverable of the Project

HW/SW integrated system

Type of Industry

Transportation

Technologies

Artificial Intelligence(AI), Internet of Things (IoT), Cloud Infrastructure

Sustainable Development Goals

Industry, Innovation and Infrastructure, Sustainable Cities and Communities

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com