Adaptive Emergency Guardian & Intelligent Safety System (AEGIS): A Proactive AI-Driven Wearable Framework for People with Vision Impairment

Assistive technologies for people with vision impairment or low vision have historically been limited to reactive systems that detect hazards only after they occur. While existing solutions provide obstacle avoidance and emergency notifications, none integrates predictive healthcare monitoring, environmental intelligence, and autonomous decision making within a unified wearable platform. This limitation creates critical gaps in preventing medical emergencies, mobility related accidents, and environmental threats before they escalate.

To address this challenge, this paper presents the Adaptive Emergency Guardian & Intelligent Safety System (AEGIS), a patent oriented next generation healthcare and mobility ecosystem designed specifically for people with vision impairment or low vision. AEGIS combines artificial intelligence (AI), biomedical engineering, computer vision, Internet of Medical Things (IoMT), edge computing, and autonomous safety analytics within a single wearable smart vest. A functional hardware prototype has been successfully developed and validated comprising an ESP32S3 microcontroller and dual HCSR04 ultrasonic sensors achieving 94.3% obstacle detection accuracy, 1.6 ms edge processing latency, and 95% emergency alert delivery success rate.

Building on this validated prototype, AEGIS introduces the Intelligent Safety and Health Integrated Threat Prediction (INSIGHT) Dynamic Risk Model a novel Mult weighted nonlinear regression framework fusing physiological and environmental telemetry from seven sensing modalities into a Unified Safety Index (Sα), with a Taylor Series Expansion based temporal forecasting engine. Simulation studies indicate that the proposed INSIGHT Dynamic Risk Model could achieve a projected sensitivity of 96.8%, a false positive rate below 1.2%, and an average predictive lead time of 4.2 minutes following future Phase II integration and experimental validation. Additional patentable innovations include a Personal Digital Twin (Random Forest + XG Boost ensemble), cardiovascular aware Smart Route Learning, a decentralized Self-Healing Community Hazard Mapping Ledger, and an on device Medical Reasoning Engine. To the best of our knowledge, AEGIS is among the first integrated wearable ecosystems to simultaneously unify all these capabilities within a single scalable, offline first platform. AEGIS has the potential to directly advance UN Sustainable Development Goals 3, 9, 10, and 11, by providing cheaper wearable assistive technology that may improve independence, safety, and quality of life for millions of people with vision impairment worldwide.