Bridging Sensory Frontiers: A Spatio-Semantic Framework for Context-Aware Assistive Technology for the Deaf and Blind

Abstract

The global rate of various kinds of sensory disabilities necessitates a paradigm shift in assistive technology (AT) from raw data to intelligent and context aware systems. Existing electronic travel aids often suffers from an “Information Gap”, giving fragmented data with no environmental situational awareness. This often leads to cognitive saturation. This study proposes the Spatio-Semantic Engine (SSE), which is a hardwareagnostic framework designed to bridge this gap through a four-layered architecture. The proposed framework integrates multimodal sensors such as LiDAR and RGBD cameras, with a Neo4j Knowledge Graph (KB) to map real-time environmental relationships. The framework removes irrelevant data in order to minimize user's cognitive overload, by using Semantic Web Rule Language (SWRL). The intelligence the system outputs as a result is delivered through cross-modal actuation. It delivers visual AR overlays for Deaf users, and spatially distributed haptic patterns for Blind/Deaf-Blind users via an arm-mounted sleeve. Mathematical models for edge-processing latency and utility-based conflict resolution are placed in order to ensure that the system navigates safely within the human kinematic reaction threshold. Overall, this framework offers a scalable, low latency, and sustainable solution for inclusive progress, especially effective in environments where resources are scarce.