OmniSence provides real-time multimodal perception, spatial vision analysis, and contextual audio-visual reasoning for intelligent environments.
OmniSence is a high-throughput multimodal intelligence engine that fuses real-time computer vision with audio stream comprehension to perceive and structure complex ambient environments.
Problem
Single-modality vision models miss critical ambient audio and spatial context needed for rich situational awareness.
Solution
OmniSence combines low-latency neural vision models and audio event detection in a unified spatial reasoning pipeline.
Features
Real-time object detection and spatial tracking
Ambient audio classification and event correlation
Zero-latency edge streaming pipeline
Spatial coordinate mapping and telemetry export
Screenshots
OmniSence spatial intelligence preview
Architecture
1High-frame rate video and audio feeds stream into ingestion pipeline
2PyTorch inference models extract spatial vectors and acoustic features
3Correlation engine matches visual anomalies with audio cues
4WebSocket server broadcasts real-time perceptual telemetry to client UI
Tech Stack
PythonPyTorchFastAPIOpenCVWebRTC
Future Roadmap
- Add 3D depth point cloud reconstruction
- Optimize models for edge microcontrollers and Jetson Nano
