MultiModal Sensing

Overview

MultiModal sensing leverages diverse data sources—RF signals, video, audio, and environmental sensors—to enable richer context-aware networking decisions.

Note

This project investigates how EdgeRIC can integrate multi-modal sensor data for intelligent network control.

Key Capabilities

  • RF Sensing: Extract environmental information from wireless signals

  • Cross-Modal Fusion: Combine multiple sensor modalities for robust inference

  • Real-time Processing: Process sensor data at RAN timescales

Applications

  • Human activity recognition for adaptive resource allocation

  • Environmental monitoring and anomaly detection

  • Enhanced localization and tracking

Architecture

The multimodal sensing pipeline integrates with EdgeRIC’s μApp framework:

  1. Sensor data collection and preprocessing

  2. Feature extraction and fusion

  3. Real-time inference engine

  4. Policy adaptation based on sensing outputs

Results

Coming soon