Recent advances in mobile hardware enable smartphones to perform real-time artificial intelligence inference using on-device neural accelerators. This paper presents the HTESGS–6DICVP architecture, an offline predictive edge safety framework designed for smartphones equipped with Neural Processing Units (NPUs). The framework integrates lightweight computer vision, contextual state modeling, probabilistic Bayesian risk estimation, and deterministic safety logic to detect and predict hazardous situations in real time. Analytical modeling demonstrates that the architecture can operate with approximately 62 ms inference latency and under 250 MB memory footprint, making it suitable for deployment on mid-range smartphones. This research framework is protected under a Provisional Patent. Application Number: 202631008397 Correspondence Address Template Corresponding Author: Anupam Sarma Affiliation: Independent Researcher / AI Developer Address: Village: Kachukata, P.O.: Tamulpur, District: Tamulpur, Assam, India, Pin Code: 781367 Email: anupamsarma997@gmail.com Innovation Focus: 6D-CV Architecture framework Patent Reference: 202631008397