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Project

Parking Control


Skill Level Area of Focus Operating System Platform/Hardware
Intermediate Computer Vision, Embedded, IoT, Smart Cities Linux DragonBoard 410c

This computer vision system is designed to detect the presence of vehicles in the regions of interest by monitoring and showing vacant parking places.

Objective

This project is intended to demonstrate the power of the DragonBoard™ 410c from Arrow Electronics in a Smart Cities solution. Rather than monitor the parking lot with a lot of sensors, you can simply use this board and a camera to cover a huge area of parking slots, utilizing the capacity of edge computing.

Materials Required / Parts List / Tools

Source Code / Source Examples / Application Executable

Source code and tutorial on GitLab

Build / Assembly Instructions

The build instructions can be found in the README file in the GitLab link. Basically, you have to install all the libraries and the application onto the board. You will need to physically install the camera pointed towards parking slots and know how to access the camera stream. The code on the repository uses an IP camera. When using an IP camera, change the IP and login info. If you use another model, you will need some OpenCV knowledge, but it's simple.

Usage Instructions

With the camera set up and the desired regions marked, run the application on the DragonBoard 410c. The app will show the image with the result and update a string with the status of each parking slot. You can send that string to the cloud or to a front-end platform like a mobile app, because all the hard work is done in the edge.

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Opinions expressed in the content posted here are the personal opinions of the original authors, and do not necessarily reflect those of Qualcomm Incorporated or its subsidiaries ("Qualcomm"). The content is provided for informational purposes only and is not meant to be an endorsement or representation by Qualcomm or any other party. This site may also provide links or references to non-Qualcomm sites and resources. Qualcomm makes no representations, warranties, or other commitments whatsoever about any non-Qualcomm sites or third-party resources that may be referenced, accessible from, or linked to this site.

Project Authors
AugustoQualcomm IoT Reference Center - FACENS
FelipeQualcomm IoT Reference Center - FACENS
Lucas MaxQualcomm IoT Reference Center - FACENS
Lucas MendesQualcomm IoT Reference Center - FACENS
Luccas SchardtQualcomm IoT Reference Center - FACENS
StephanieQualcomm IoT Reference Center - FACENS

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