Edge Computing & Real-time Streaming
Instant Intelligence at the Network Edge
Real-time AI processing with cutting-edge edge computing technology
processing latency
processing speed
energy savings
Edge Hardware Platforms
NVIDIA Jetson
High-performance AI chips for edge computing
- Nano: 472 GFLOPS
- Xavier NX: 21 TOPS
- Orin: 275 TOPS
Intel Edge
Intel edge computing solutions
- Intel NUC
- Neural Compute Stick
- Movidius VPU
Specialized AI Chips
Purpose-built AI processing chips
- Google Coral TPU
- Hailo AI Processors
- Apple Neural Engine
ARM-based Edge
Power-efficient ARM-based solutions
- Raspberry Pi 4/5
- NVIDIA Jetson Nano
- Qualcomm Snapdragon
FPGA Edge
FPGA solutions for hardware customization
- Xilinx Zynq UltraScale+
- Intel Arria/Stratix
- Lattice FPGAs
Cloud Edge Services
Edge computing services from cloud providers
- AWS IoT Greengrass
- Azure IoT Edge
- Google Anthos
Model Optimization for Edge
C Compression Techniques
Quantization
Reduce numerical precision from 32-bit to 8-bit or lower
Pruning
Remove unimportant connections from neural networks
Knowledge Distillation
Transfer knowledge from large models to smaller ones
F Optimization Frameworks
NVIDIA TensorRT
Intel OpenVINO
TensorFlow Lite
ONNX Runtime
Real-time Processing Architecture
Latency Reduction Techniques
Pipeline Processing
Divide processing into parallel pipeline stages
Frame Skipping
Skip unnecessary frames to maintain speed
ROI Processing
Process only regions of interest
Memory Optimization
Zero-copy memory management
Streaming Protocols
RTMP (Real-Time Messaging)
Latency: 3-5 seconds | Live streaming
WebRTC (Web Real-Time Communication)
Latency: <100ms | Ultra real-time
RTSP (Real Time Streaming Protocol)
Latency: 1-2 seconds | CCTV systems
UDP (User Datagram Protocol)
Latency: <1ms | Internal processing
Ready to Build Real-time Edge AI Systems?
Consult our edge computing and real-time streaming experts