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
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
Type of Industry
Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Intel Movidius NCS | Equipment | 2 | 12600 | 25200 |
| Raspberry Pi | Equipment | 2 | 6300 | 12600 |
| Camera | Equipment | 2 | 4000 | 8000 |
| SD card | Equipment | 2 | 1000 | 2000 |
| Total in (Rs) | 47800 |
If you need this project, please contact me on contact@adikhanofficial.com
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