Staff Presence Monitoring at Service Counters

In high-traffic environments such as restaurants, cafes, and food courts, maintaining a consistent staff presence at customer service counters is vital for efficiency and customer satisfaction. But in busy or understaffed situations, it's easy for counters to go unattended—leading to poor service, longer wait times, and lost business.

In this blog, we’ll walk through a practical AI-based solution that uses real-time object detection to determine whether a staff member is present at a designated service counter. This solution is built using the YOLOv8 model from Ultralytics, integrated with OpenCV for video processing.

Problem Statement

Staffing issues at customer service counters can directly impact customer experience, reduce operational efficiency, and damage a brand's reputation. Whether it's a restaurant, food court, or quick-service outlet, unattended counters can lead to customer frustration, longer wait times, and lost revenue.

According to operational audits and customer feedback surveys, one of the most frequent issues in retail and hospitality is the absence of staff at service points during peak hours—often unnoticed by managers until it’s too late.

Key challenges businesses face:

• Staff temporarily leaving counters unattended without alerting supervisors

• Inability to monitor multiple counters or service points in real time

• Human oversight limitations, especially during rush hours or staff shortages

• Lack of reliable documentation for reviewing staff behavior or addressing complaints

  
  

These challenges highlight the need for an automated system that can monitor and log staff presence at counters, ensuring accountability and enabling prompt action.

How AI-Based Presence Detection Works

Modern AI surveillance systems leverage computer vision to automatically monitor staff presence at service counters. Using state-of-the-art object detection models like YOLO (You Only Look Once), these systems can detect and track individuals in real time with high accuracy.

These AI systems can perform:

• Staff presence detection: Automatically determine whether at least one staff member is present within the designated service area

• Zone-based monitoring: Define specific counter regions (zones of interest) and check for activity only in those areas

• Real-time alerts: Instantly notify managers if a counter is left unattended for a defined duration

• Automated video logging: Record and log presence data over time for audit, analysis, or compliance reporting

By eliminating manual supervision and offering continuous, objective monitoring, AI-powered systems help ensure that customer service points remain staffed—improving operational efficiency and customer satisfaction.

Implementation Benefits for Restaurants

Improved Customer Service

AI-powered presence monitoring ensures that service counters are never left unattended, leading to faster customer response times and a smoother dining experience.

Operational Oversight

Managers gain real-time visibility into staff availability without constantly watching surveillance footage or walking the floor.

Automated Record-Keeping

The system logs presence data automatically, providing valuable documentation for internal reviews, shift planning, and accountability.

Workforce Optimization

By identifying unattended counters or inefficient staffing patterns, restaurants can optimize staff deployment during peak and off-peak hours.

Reduced Human Error

AI systems offer consistent, unbiased monitoring 24/7—something that's difficult to achieve with manual supervision alone.

Practical Applications

Presence detection at service counters is already being adopted across multiple sectors:

• Quick-service restaurants use it to ensure staff are available during high-traffic hours

• Hotel front desks monitor staff availability to improve guest satisfaction

• Retail stores use it to keep checkouts properly staffed during peak shopping periods

• Cafeterias and food courts track counter activity to streamline service flow

• Banks and service centers ensure that teller counters remain attended during business hours

By integrating AI-based presence monitoring, restaurants and similar businesses can maintain service standards, improve accountability, and elevate the overall customer experience.

Model Used

For this project, we used a pre-trained YOLOv8s model (yolov8s.pt) from the Ultralytics library. YOLOv8s is a lightweight, real-time object detection model capable of accurately detecting people and objects with minimal computational overhead.

We did not use any custom dataset for training. Instead, we leveraged the model’s built-in capability to detect people (class 0 – person) to identify staff presence at service counters.

This approach eliminates the need for manually labeling data or training a custom model, making it ideal for rapid deployment and proof-of-concept solutions.

How It Works

• The system continuously analyzes frames from a video feed

• A predefined rectangular region marks the counter area of interest

• If a “person” is detected within this region, the system marks the counter as “Present”

• If no person is detected in the zone, it displays “Absent”

This simple but effective setup provides actionable insights into whether staff are present at designated service points—without the need for additional datasets or complex training processes.

Result

Full code is available at the following link:

Staff_presence_monitoring.pdf

Download PDF • 127KB

Get Help When You Need It

Building a staff presence detection system may seem straightforward at first, but challenges can arise—especially when working with real-time video processing, model tuning, or integrating detection logic into larger operational workflows like restaurant POS or staff management systems.

Don’t hesitate to seek expert assistance when you're stuck with:

• Optimizing video analysis for smoother real-time detection

• Managing multiple camera feeds

• Defining dynamic presence zones

• Automating reporting and alert systems

If you’re working on a staff presence monitoring system and need hands-on support, CodersArts specializes in both academic and industrial computer vision solutions.

Whether you're a student building a project with YOLO and OpenCV or an enterprise deploying a real-time monitoring system, their team can assist with:

• Model selection and video pipeline optimization

• Custom detection zones for different service areas

• Scalable deployment in restaurants or retail setups

• Integration with dashboards or compliance reporting tools

Visit www.codersarts.com or reach out via contact@codersarts.com to get started with expert help.