AI CCTV Pizza Outlet Event Detection

# Job Title: AI Camera Vision Developer – POS Bill Slip Detection & Pizza Customer Collection Tracking

**Project Budget:** ₹7,000 (Fixed Price)
**Timeline:** 2 Days (Urgent)
**Project Type:** AI / Computer Vision / Video Analytics

### Project Overview
We are looking for an experienced AI/Computer Vision developer to develop and implement a camera-based AI solution for a pizza outlet.

The solution should identify two specific activities using existing CCTV camera footage:

### 1. POS Bill Slip Detection
- Detect when a printed bill/order slip comes out of the POS billing machine.
- Identify and count each slip generated by the POS machine.
- Record the timestamp of every detected slip.
- Avoid duplicate counting of the same slip.

### 2. Pizza Customer Collection Tracking
- Identify when a customer collects a pizza/order from the staff at the billing counter.
- Detect the interaction between staff and customers during order handover.
- Count the total number of successful pizza/order handovers.
- Record the timestamp of each collection event.
- Avoid duplicate counting of the same customer collection.

### Technical Requirements
- AI-based computer vision using CCTV/IP camera footage.
- Object detection and tracking.
- Real-time or recorded video processing, depending on the existing system architecture.
- Integration with our existing AI camera vision system.
- Accurate event detection and counting.
- Structured output containing event type, timestamp and count.

### Data & Support
- We will provide the required video footage, reference data and other necessary inputs.
- Our technical team will support the developer during implementation and integration.
- The developer must be able to implement the solution within our existing system.

### Deliverables
1. Working AI model/logic for POS slip detection.
2. Working AI model/logic for customer pizza collection tracking.
3. Integration into our existing AI camera vision system.
4. Event-wise counting and timestamp logging.
5. Testing and demonstration of the implemented solution.

### Acceptance Criteria & Payment
**Final sign-off will be provided only after:**
- Both use cases are successfully implemented in our system.
- The solution achieves a minimum of **95% detection accuracy** on the agreed test dataset and validation methodology.
- Duplicate and missed detections are evaluated during testing.
- Our technical team validates the results in the actual deployment environment.

**Important:** Payment approval and final project sign-off will be subject to successful implementation and validation of 95%+ accuracy.

### Required Skills
- Python
- OpenCV
- YOLO / Object Detection
- Computer Vision
- Object Tracking (DeepSORT / ByteTrack)
- AI Video Analytics
- CCTV / RTSP Camera Integration
- Model Optimization and Deployment

### To Apply
Please share:
1. Relevant experience in AI camera vision and object detection.
2. Examples of similar projects delivered.
3. Your proposed technical approach.
4. Confirmation that you can complete the assignment within 2 days and within the ₹7,000 budget.

**We are looking for someone who can deliver a working implementation, not just a model or proof of concept.**