AI-Powered Image Processing

[DevyManish]

AI-Powered Image Processing for Monitoring Counter Services

AI system will analyze real-time CCTV footage to detect various events such as customer congestion, idle counters, long waiting times, and other service bottlenecks.

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1. Objectives of AI Monitoring

Purpose:

• Automated Monitoring
• Wait Time
• Service Time
• Employee Score
• PO Leaderboard

Key Detection Targets:

• Customer Congestion: Detect high-density areas where customers are waiting too long.
• Idle Counters: Detect counters that are left unattended or inactive for extended periods.
• Queue Length Estimation: Estimate the number of people waiting and their positions in the queue.
• Customer Emotions (Optional): Detect customer emotions like frustration using facial expression recognition to infer service satisfaction.

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2. Machine Learning Algorithms

Object Detection (Counters, Staff, and Customers)

Algorithm:

• YOLO (You Only Look Once) or Faster R-CNN
  • Reason: Both YOLO and Faster R-CNN are well-suited for real-time object detection tasks. YOLO is faster and more appropriate for scenarios requiring real-time inference, while Faster R-CNN provides more accurate bounding box predictions.
  • Output: Detect and classify counters, customers, and staff in each frame of the CCTV feed.

Training Dataset:

• Use a custom dataset of annotated post office service areas, including images of counters, customers, and post office staff.
• Pre-trained model: Start with a pre-trained YOLO/Faster R-CNN model on a general object detection dataset (e.g., COCO) and fine-tune it on post office-specific data.

Training Parameters:

• Optimizer: Adam or SGD
• Learning Rate: 0.001 (tune during experimentation)
• Epochs: 50-100 (with early stopping if validation loss stagnates)
• Batch Size: 16

Evaluation Metrics:

• Precision/Recall: Monitor precision and recall for detecting counters, customers, and staff.
• Mean Average Precision (mAP): mAP should be above 0.85 for accurate detection in service monitoring scenarios.

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[sahilDas04]

Assign me this !

[pratyushsingha]

ok