NVIDIA’s Jetson series of AI hardware, with its high performance, low power consumption, and powerful AI inference capabilities, is very suitable for tasks in the security field such as intelligent video analytics, facial recognition, and abnormal behavior detection. The table below outlines some typical application scenarios and hardware characteristics of Jetson in security:
| Application Area | Specific Application Scenarios | Relevant Jetson Hardware Features |
|---|---|---|
| Intelligent Video Surveillance (NVR) | Real-time video stream analysis, detecting anomalies like intrusion, unattended objects, fire, and triggering alarms. | – High-Performance Computing: Jetson AGX Orin, Xavier NX can handle multiple video streams. – AI Acceleration: Integrated GPU accelerates deep learning model inference. |
| Facial Recognition & Access Control | Identifying individuals at access points or in public areas for security management and control. | – Edge Computing Capability: Processes data directly on the device for quick response and privacy protection. |
| Behavior Analysis & Anomaly Detection | Detecting behaviors such as falling, perimeter intrusion, or unusual crowding; applicable in communities, nursing homes, etc. | – Sensor Support: Can connect to multiple cameras. – Pre-trained Models: Some platforms offer AI SDKs to accelerate application development. |
| Traffic Monitoring & License Plate Recognition | Identifying vehicles, monitoring traffic flow, and performing license plate recognition for intelligent traffic management. | – Industrial-Grade Design: Some Jetson-powered devices feature wide-temperature operation, dust and water resistance, suitable for harsh outdoor environments. – PoE Functionality: Can power cameras and transmit data directly via Ethernet cables, simplifying wiring. |
Deployment and Selection
Now that you understand what Jetson can do, you might also be interested in how to deploy it and choose the right model. Here are some deployment patterns and key selection points for your reference:
- Deployment Mode: AI applications in the security field primarily use the Edge Computing model. This means data is processed directly on the Jetson device near the camera, offering advantages like low response latency, reduced network bandwidth pressure, and higher data privacy.
- Hardware Selection Considerations
- Computing Performance: Choose based on the number of video streams to be analyzed and the complexity of the AI models. Jetson AGX Orin offers the highest performance, suitable for large projects; Jetson Xavier NX is a robust mid-range option; Jetson Nano is suitable for lightweight applications.
- Connectivity & Expansion: Pay attention to the number of PoE ports (determines how many cameras can be connected directly), USB and network interfaces, etc.
- Environmental Suitability: For outdoor or harsh conditions, select products with industrial-grade design features like wide-temperature operation, ingress protection (IP rating), and vibration resistance.
- Development & Management: Utilize NVIDIA’s JetPack SDK and partner-provided low-code AI platforms (like ADLINK’s EVA SDK) to accelerate development. Also, consider whether the device supports remote management tools for easier maintenance.
- Deployment Practice Reference
Deploying open-source Network Video Recorder (NVR) systems, such as Frigate or an AI NVR based on NVIDIA DeepStream, on Jetson devices is a common practice. These systems support real-time object detection and can often be configured and managed conveniently via a web interface.
