u/Firm-Author8122

Hi everyone,

I’m currently working on an edge AI + IoT based monitoring project and planning to use the NVIDIA Jetson Orin NX for real-time processing.

The project involves:
• Multiple environmental sensors
• Camera-based monitoring
• Real-time anomaly detection
• Edge inference with minimal cloud dependency
• Continuous monitoring in a large indoor environment

I would like advice from people experienced with Jetson deployments.

Main questions:

1. Is Jetson Orin NX a good choice for handling multiple sensor inputs and camera streams simultaneously?
2. What camera modules are recommended for low-light indoor monitoring?
3. Is Docker recommended for Jetson deployment?
4. Best practices for optimizing TensorRT inference?
5. Suggested architecture for combining ESP32 sensor nodes with Jetson?
6. MQTT vs other communication protocols for scalable deployments?
7. Thermal and power considerations for 24/7 operation?
8. Recommended lightweight object detection models for edge devices?
9. Is hybrid edge + cloud synchronization better than fully edge-based architecture?

Current stack idea:
• Jetson Orin NX
• ESP32
• Python
• OpenCV
• TensorRT
• MQTT
• FastAPI

Would appreciate any deployment tips, architecture suggestions, or lessons learned from real-world projects.

Thanks!