Unique Person Counting in an Exhibition

Problem

• There are no reliable ways to track unique visitor tracking across multi-day events.
• No live analytics for organizers, especially during peak hours.
• Manual counting or ticket scanning methods are slow and error prone.
• Current methods lack deep insights into visitor behavior. Also, in engagement and demographics.

Solution

We developed a computer vision-based people counting solution that detects and counts unique visitors in real time at exhibitions and expos.

• The solution uses facial recognition for events to identify individuals uniquely across the day.
• Captures demographic details like age, gender and clothing color.
• Enables real time people counting with live dashboards for organizers.
• Provides visual analytics including heat maps, peak hours, and visitor flow patterns.
• Offers cloud-based access to visitor logs, analytics reports and historical trends.

Implementation Challenges

• Differentiating between repeat and new visitors using computer vision facial recognition
• Ensuring high accuracy in crowded and dynamic environments.
• Handling varied lighting, angles and occlusions at different booths or zones.
• Processing real-time data without delays during high footfall.
• Maintaining privacy and data compliance with facial recognition for events.

Key Features

• Unique visitor tracking with face-based differentiation.
• High-accuracy people counting computer vision systems.
• Real-time demographic detection and engagement monitoring.
• Central dashboard for real time people counting insights.
• Scalable solution for large-scale exhibitions and expos.
• Cloud-accessible reports and logs for post-event analysis.
• Privacy-aware computer vision facial recognition with event-focused configurations.