Smart Healthcare Assistant for Maternal and Child Care Supporting Rural Health Facilitators
Keywords:
Artificial intelligence, ASHA workers, Child health monitoring, High-risk pregnancy prediction, Immunization tracking, Maternal healthcare, Mobile health (mHealth), Voice-based interfacesAbstract
Maternal and child healthcare in rural and semi-urban regions continues to face considerable difficulties due to inadequate access to quality medical facilities and limited technological infrastructure. Community health workers such as ASHA and Anganwadi personnel are essential in delivering primary care services; however, their effectiveness is often restricted by reliance on manual record-keeping and the absence of real-time decision-making support. This study examines the application of Artificial Intelligence (AI) and digital healthcare technologies in maternal care, with particular emphasis on risk assessment, continuous health monitoring, and clinical decision support systems. Existing research indicates that machine learning techniques and mobile health (mHealth) solutions significantly contribute to early risk identification, improved data management, and better communication between healthcare providers and patients. Despite these advancements, several challenges persist, including limited usability for low-literacy users, insufficient multilingual and voice-based interaction capabilities, and a lack of integrated systems that ensure continuity of care. Therefore, there is a strong need for a comprehensive and user-centric platform that combines AI-powered analytics, voice-enabled interfaces, automated notification systems, and efficient immunization tracking. Such a solution can enhance the productivity of healthcare workers and improve overall maternal and child health outcomes.
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