A Voice-Driven AI Healthcare Ecosystem for Intelligent Screening, Prevention, and Emergency Response

Authors

  • Pranay Bhawsar Department of Computer Science & Engineering, Indore Institute of Science and Technology, Indore, Madhya Pradesh, India 
  • Praveena Joshi Department of Computer Science & Engineering, Indore Institute of Science and Technology, Indore, Madhya Pradesh, India 
  • Shreyas Pagare IIST

DOI:

https://doi.org/10.71143/np28x512

Abstract

Healthcare systems in rural and semi-urban areas continue to face problems such as late medical care , less awareness, wrong or misinformation during outbreaks, shortage of medical care professionals, and low emergency response. These issues often lead to loss of lives, as clearly observed during the COVID-19 pandemic. To solve this problem we develop MIRA, an AI-driven, voice-activated healthcare ecosystem designed to provide early screening, preventive alerts, virtual voice-activated medical assistant, and emergency response through a single platform. MIRA integrates three core technology/phases: a voice-enabled screening assistant, the Raksha System for preventive outbreak detection and awareness, and the Suraksha System for emergency coordination including virtual doctor connectivity through video call and ambulance support which all to short out the shortest way. The system emphasizes accessibility through multi language voice support, offline and low-internet functionality, and simple user-friendly interfaces suitable for diverse populations.  MIRA uses the approach name rule-based logic supported by basic machine learning models to know health risks and provide correct responses. spread awareness, reduce emergency response time during emergencies, and grow the healthcare sector/environment

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Published

30-10-2026

How to Cite

Pranay Bhawsar, Praveena Joshi, & Pagare, S. (2026). A Voice-Driven AI Healthcare Ecosystem for Intelligent Screening, Prevention, and Emergency Response. International Journal of Research and Review in Applied Science, Humanities, and Technology, 3(4), 31-34. https://doi.org/10.71143/np28x512