AI Edge Computing

Intelligence at the Edge

FANYE develops AI-powered embedded systems that process data locally, reducing latency, bandwidth, and cloud dependency. Our solutions enable real-time inference on resource-constrained devices.

Edge AI Platforms

• Ingenic T41/T31 — High-performance AI vision processors with integrated ISP
• Rockchip RK3588/RK3568 — Powerful edge AI for complex applications
• ESP32-S3 — AI acceleration for voice and sensor applications
• STM32N6 — Neural processing unit for low-power AI
• Google Coral — Edge TPU for demanding AI workloads

Success Story: BirdCam AI

We developed an AI-powered wildlife camera that recognizes 200+ bird species in real-time. The system uses an Ingenic T41 processor with a custom-trained CNN model. Features include species identification, audio playback of bird calls, and mobile app integration. 3,200+ units shipped with 95.3% recognition accuracy.

AI Applications We Develop

• Wildlife & Nature Monitoring — Bird species recognition, animal detection, activity logging
• Industrial Vision Inspection — Defect detection, quality control, assembly verification
• Audio Analytics — Sound classification, anomaly detection, voice commands
• Facial Recognition — Secure access control, attendance systems
• Object Detection & Tracking — People counting, vehicle detection, security monitoring
• Sensor Fusion — Combining vision, audio, and sensor data for context-aware decisions

Technical Implementation

• TensorFlow Lite / PyTorch Mobile model optimization
• INT8 quantization for reduced memory and power
• NPU/TPU acceleration for real-time inference
• Model pruning and distillation for edge deployment
• Custom dataset collection and annotation
• Continuous learning and model improvement pipeline

Hardware Integration

• Camera modules with ISP for image quality optimization
• Microphone arrays for audio capture and beamforming
• Low-power design for battery-powered AI devices
• Solar integration for remote deployments
• 4G/LTE or LoRa for connectivity where needed

Success Metrics

• 95.3% recognition accuracy on 200+ bird species
• 120ms inference time per frame on Ingenic T41
• 3-5 day battery life on solar-rechargeable system
• Deployed in 30+ US states and 8 countries

Start Your Edge AI Project

Ready to add intelligence to your device? Contact our AI engineering team to discuss your application.