AI-Based Bag Counting at Entry & Exit Gates
Accurate. Automated. Tamper-Proof.
Intelgic’s AI-powered camera counting solution automates the counting of flour bags and other industrial bags at entry and exit gates using advanced computer vision.
By connecting RTSP-enabled cameras directly to the AI software, every bag is detected, tracked, and counted frame by frame—eliminating manual errors, losses, and disputes.
Accurate counting of flour bags, cement bags, fertilizer bags, food grain sacks, and other packaged materials at entry and exit gates is a critical operational requirement for factories, warehouses, and logistics hubs. Traditionally, this counting has been done manually or through basic sensors—both of which are prone to errors, manipulation, and inefficiencies.
Intelgic offers a robust AI- and camera-based bag counting solution that automates this process using advanced computer vision and deep-learning algorithms. The system ensures reliable, tamper-proof, and auditable counting of bags moving through gates during loading, unloading, dispatch, and receipt operations.
Challenges in Traditional Bag Counting
Manual or semi-automated counting methods face several limitations:
- Human error during high-speed loading/unloading
- Inconsistent counts during shift changes or night operations
- Difficulty counting bags when they are close together or partially overlapping
- No visual audit trail for dispute resolution
- Delayed reconciliation between dispatch and receipt records
AI-based vision systems directly address these challenges by observing every bag visually and counting them digitally in real time.
Intelgic’s AI Camera Counting Solution – Overview
Intelgic has developed a field-proven bag counting solution designed specifically for industrial environments.
Core Principle
- Fixed cameras are installed at entry and exit gates or loading/unloading zones
- Cameras stream live video to the AI software using RTSP (Real-Time Streaming Protocol)
- The software processes the video frame by frame
- AI models detect, track, and count every bag crossing a defined virtual boundary
This approach ensures high accuracy even under continuous operations.
System Architecture
Camera Integration via RTSP
- IP cameras with RTSP support connected to AI software
- Supports multiple cameras simultaneously
- No dependency on proprietary hardware
- Works with existing CCTV or new industrial cameras
Real-Time Video Processing
- The software ingests the RTSP stream frame by frame
- Each frame is analyzed using deep-learning detection models
- Bags are identified based on shape, size, texture, and motion patterns
Intelligent Bag Tracking
- Once detected, each bag is assigned a unique tracking ID
- The system tracks the bag across successive frames
- Counting is triggered only when the bag crosses a predefined counting line or region
- Double counting
- Missed counts due to partial visibility
- False counts from background movement
Accurate Counting Logic at Entry & Exit Gates
The system allows users to define virtual counting zones:
Entry Gate Zone
Bags entering the premises
Exit Gate Zone
Bags leaving the premises
Only bags that:
- Appear fully in the frame
- Move in the correct direction
- Cross the virtual boundary
are added to the count.
This directional intelligence is essential for:
- Dispatch vs receipt tracking
- Preventing reverse movement errors
- Ensuring clean reconciliation data
Handling Real-World Industrial Scenarios
Intelgic’s AI models are trained to handle typical industrial challenges:
Bags moving close to each other
Workers walking alongside bags
Partial occlusions during loading
Different bag sizes and materials (PP, jute, paper, laminated sacks)
Variable speeds of movement
The software focuses only on bag-specific visual signatures, ignoring non-relevant objects.
Software Interface & User Experience
The Intelgic counting software provides:
Live camera view with AI overlays
Real-time counters for entry and exit
Shift-wise, batch-wise, and date-wise summaries
Manual correction and validation options (role-based)
Visual playback for audit and verification
Every counted bag is backed by video evidence, enabling full traceability.
Data Logging, Reports & Integration
The system automatically stores:
- Time-stamped counts
- Camera ID and gate location
- Entry vs exit classification
Integration Capabilities
- ERP / WMS / Dispatch systems
- Cloud dashboards
- CSV / API data export
This enables:
- Automated reconciliation with delivery challans
- Stock movement validation
- Reduction of disputes with transporters
Deployment Models
Intelgic offers flexible deployment options:
Edge-based AI processing (on-premise GPU)
Hybrid edge + cloud analytics
Remote configuration and support
Scalable from:
Single gate installation
To multi-gate, multi-plant deployments
Key Benefits
Near-100% accurate bag counting
Eliminates manual dependency
Real-time visibility of material movement
Visual proof for audits and disputes
Faster loading/unloading reconciliation
Improved operational transparency
Typical Use Cases
Flour mills
Cement and building material plants
Fertilizer and chemical factories
Food grain warehouses
Logistics yards and dispatch centers
Frequently Asked Questions
1. What types of bags can the system count?
The solution can count flour bags, cement bags, fertilizer bags, food grain sacks, chemical bags, and other industrial packaging formats made of PP, jute, paper, or laminated materials.
2. How does the system connect to cameras?
The system connects directly to surveillance cameras using RTSP (Real-Time Streaming Protocol). The AI software receives the live video stream and processes it frame by frame for accurate detection and counting.
3. Does the system require special cameras?
No. Any standard IP camera that supports RTSP and provides a stable video feed can be used. Existing CCTV infrastructure can often be reused.
4. How does the system ensure accurate counting?
Each bag is:
- Detected using AI models
- Assigned a unique tracking ID
- Counted only when it crosses a predefined virtual counting line or zone
This avoids double counting, missed counts, or false triggers.
5. Can it differentiate between entry and exit counting?
Yes. Separate virtual zones can be configured for entry gates and exit gates, allowing the system to distinguish inward and outward material movement accurately.
6. What happens if bags move very close to each other?
The AI model is trained to handle closely moving or partially overlapping bags by analyzing motion, shape, and continuity across frames.
7. Does worker movement affect counting accuracy?
No. The system is trained to recognize and count bags only, ignoring human movement, forklifts, and other non-relevant objects.
8. Is there a visual record of counted bags?
Yes. Every count is backed by video footage. Users can replay recordings for audits, verification, and dispute resolution.
9. Can the data be integrated with ERP or dispatch systems?
Absolutely. The system supports data export and API-based integration with ERP, WMS, inventory, and dispatch management systems.
10. Is the solution cloud-based or on-premise?
Both options are available:
- Edge (on-premise) AI processing
- Hybrid edge + cloud analytics
Deployment depends on customer IT and security preferences.
11. How scalable is the solution?
The system can scale from a single gate with one camera to multiple gates, warehouses, and plants with centralized reporting
12. Where is this solution commonly used?
- Flour mills
- Cement and building material plants
- Fertilizer and chemical factories
- Food grain warehouses
- Logistics and dispatch yards
