Deploy machine learning systems that use ambient RF signals for high-accuracy location where GPS fails.
Services
AI for RF-Based Positioning Systems
Engineering machine learning solutions that use RF signal fingerprints (Wi-Fi, Bluetooth, Cellular) for high-accuracy indoor and urban positioning, surpassing traditional GPS limitations.
INDOOR & URBAN POSITIONING
AI for RF-Based Positioning Systems
Traditional GPS is unreliable indoors and in dense urban canyons. Our AI systems analyze ambient RF signal fingerprints—from Wi-Fi, Bluetooth, and Cellular networks—to deliver sub-meter positioning accuracy without dedicated infrastructure.
We engineer deterministic location intelligence from probabilistic signal data, enabling new applications in logistics, smart buildings, and security.
- Key Deliverables:
Wi-Fi/BLEfingerprinting models, cellular signal triangulation AI, and hybrid sensor fusion algorithms. - Measurable Outcomes: 90%+ accuracy in complex multi-floor environments, <100ms inference latency for real-time tracking, and seamless integration with existing enterprise systems.
- Technical Approach: We develop custom convolutional neural networks (CNNs) and transformer-based models trained on proprietary RF I/Q data to classify unique spatial signatures.
This service is part of our broader Radio Frequency (RF) Machine Learning pillar, which includes solutions for RF Signal Intelligence AI Consulting and Predictive Cellular Network Operations AI. For enterprises requiring data sovereignty, explore our Sovereign AI Infrastructure Development services.