AI and Accessibility Advances in 112 Emergency Call Management

Abstract

This article explores the role of artificial intelligence (AI) in enhancing accessibility for persons with disabilities within Europe’s 112 emergency communication systems. Despite regulatory and ethical commitments to inclusion, individuals with hearing, speech, cognitive, and mobility impairments continue to encounter significant barriers when attempting to request emergency assistance. These barriers range from non-adaptive voice-based systems to high-stress environments that limit effective communication. This research responds to a critical gap between inclusive design principles and their real-world implementation in emergency services. Using the SALSA methodology (Search, Appraisal, Synthesis, Analysis), this study systematically reviews literature, EU policy documents, and pilot initiatives conducted between 2020 and 2025. It categorizes findings into key domains where AI shows significant impact: real-time transcription, emotion detection, chatbot support, and multimodal interfaces. Case studies such as the ODIN 112 project in Romania and the EENA–Corti cardiac arrest detection pilot is analysed alongside conceptual and ethical frameworks from EU bodies. The results suggest that while AI technologies hold transformative potential—offering personalized, scalable, and context-sensitive support—many tools remain in pilot phases and face limitations related to linguistic coverage, stress-induced error, data privacy, and ethical oversight. The research highlights the importance of inclusive, co-designed systems and calls for cross-sector collaboration to scale AI solutions ethically and effectively. This article contributes to the evolving discourse on accessible public service delivery by bridging theoretical models with empirical evidence, offering insights into how AI can support more humane and equitable emergency response systems across Europe. UDC: 355.588:004.8; JEL: O33, I18, H83