Portable Artificial Intellegence Safety Apparatus with Digital Twin Integration, Adaptive Micro-Mobility Collision Avoidance, and Decentralized Edge Training

Abstract

A portable artificial intelligence safety apparatus and associated hazard detection device are disclosed. The apparatus includes a single-board computer with a hardware AI accelerator and a multi-modal sensor suite comprising an optical camera, solid-state LiDAR, and thermal infrared camera. A modular mounting architecture enables attachment to diverse vehicle types. Fused sensor data is processed by an ensemble of object detection models and a situational rules engine to compute time-to-collision, detect traffic congestion, and classify objects, including trucks, trees, animals, humans, and stationary structures. The system issues multi-modal alerts and monitors driver rule adherence and drowsiness to form driver-specific behavioral profiles, which may be correlated with geolocation data for traffic planning. In some embodiments, a V2X module and infrastructure data receiver refine safety metrics. A companion device supports localized model evolution via a paired mobile device, enabling deployment of updated models without cloud connectivity.

Dependencies are inferred from the claim text.