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Project title:
UVra Queue AI — AI-Powered Queue Detection System
Role:
AI / Computer Vision Developer
Description:
An AI-powered queue monitoring system designed to detect people in queues, analyse crowd conditions and estimate waiting times from camera feeds. The project combines computer vision with a web-based monitoring system to help businesses understand queue activity and respond to congestion.
Key features to show: YOLO-based person detection, real-time camera/video analysis, queue monitoring, estimated waiting times, alerts, analytics/dashboard, multi-camera concept, reporting and heatmap/traffic insights.
The network for creativity
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Creatives on Contra have earned over $150M and we are just getting started
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Project Overview
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Key Responsibilities
Performed web research and collected relevant information.
Entered, updated, and organized data in spreadsheets.
Built and maintained structured contact lists.
Prepared and organized basic digital documents.
Managed files and information using a clear folder structure.
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Skills:
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Tools:
Microsoft Excel • Google Sheets • Google Docs • Google Drive • Google Chrome
Great overview. Data organization, accurate spreadsheet management, and structured documentation are often what keep day-to-day operations running smoothly. Clear processes and attention to detail can make a big difference in administrative workflows.