Overview
Hanwha QNF-C9010V 12MP Outdoor AI Fisheye Camera
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Bundle Summary
Overview
Hanwha QNF-C9010V 12MP Outdoor AI Fisheye Network IP Camera
The Hanwha QNF-C9010V delivers exceptional panoramic surveillance coverage for large outdoor areas with a single camera installation. Built on a 12-megapixel fisheye sensor with a fixed 1.76 mm focal length and F1.8 aperture, this camera captures a complete 185° field of view—eliminating blind spots and reducing the need for multi-camera deployments. Its 3008 × 3008 maximum resolution at 20 fps ensures forensic-quality detail for incident investigation and evidence preservation in high-security outdoor applications.
Key Features
- 12MP fisheye sensor with 185° panoramic field of view
- 3008 × 3008 resolution at 20 fps for fine forensic detail
- Fixed 1.76 mm focal length with F1.8 aperture
- AI-powered object detection: people, vehicles, and attribute classification
- H.265, H.264, and MJPEG codec support for optimized bandwidth
- CloudConnector integration for OnCloud and SightMind platforms
- Purpose-built for outdoor, high-demand environments
Technical Highlights
The QNF-C9010V's ultra-wide 185° panoramic lens eliminates the need for pan-tilt-zoom repositioning or multiple overlapping cameras, reducing installation complexity and maintenance overhead. The combination of 12MP resolution and intelligent video compression ensures that footage remains crisp and detailed while keeping bandwidth and storage costs manageable across large-scale deployments.
Advanced AI analytics embedded in the camera enable real-time classification of people, vehicles, and behavioral attributes, reducing false alarms and accelerating event search during investigations. This intelligence is particularly valuable in high-volume surveillance environments where manual review is impractical.
Cloud Integration & Scalability
Native CloudConnector support enables seamless integration with cloud-based management platforms including OnCloud and SightMind. This architecture simplifies multi-site deployments, centralizes monitoring and alerting, and provides flexible storage options without requiring on-premises NVR infrastructure.
Applications
- Perimeter security for large outdoor facilities and campuses
- Parking lot and open-area surveillance
- Industrial site monitoring
- Transportation and logistics terminals
- Smart city and municipal surveillance
- High-security outdoor environments requiring forensic-grade video

The QNF-C9010V represents a significant operational advantage over traditional multi-camera panoramic solutions. By delivering full 185° coverage from a single mounting point, it reduces installation labor, simplifies cable management, and eliminates the geometric distortion and overlap challenges inherent in stitched multi-camera arrays. The 12MP sensor provides genuine forensic resolution—not interpolated—essential for facial recognition and vehicle plate identification at distance.
The embedded AI engine delivers measurable value in high-volume surveillance: intelligent filtering reduces alert fatigue while accelerating forensic search through attribute-based indexing. Combined with H.265 codec efficiency, the camera's bandwidth profile remains competitive with lower-resolution traditional cameras, making it cost-effective for wide-area deployments. CloudConnector integration future-proofs investments by supporting modern cloud-first security architectures without legacy NVR dependency.
System Design, Deployment & Technical Support
Support services and planning resources for commercial surveillance, access control, and infrastructure deployments.
Fixed scope • Fixed price
System Design Assistance
- Get help validating product compatibility
- Coverage requirements
- Storage planning and deployment architecture before you buy.
Deployment & Configuration Support
- Access fixed-scope support for rollout planning
- User setup guidance
- Migration and system standardization across single-site or multi-site deployments
Guides, Tools & Calculators
- PoE requirements
- Storage retention
- Camera selection and deployment methodology