AI-Enabled Multilingual Telemedicine Platform for Rural Healthcare with Low-Bandwidth Support

Abstract

Rural and semi-urban residents often put off medical care because the nearest qualified doctor is hours away, consultation fees are unpredictable, and existing health apps are difficult to use in their language. This paper presents a web-based multilingual telemedicine platform with three role-specific interfaces, for patients, doctors, and administrators, that remains usable on low-bandwidth rural internet connections. Patients describe their symptoms in their own language to an AI-driven symptom checker, which applies natural-language processing and a trained classification model to suggest likely conditions and self-care guidance without any travel. Once a condition is predicted, a recommendation engine orders nearby hospitals and doctors according to distance, consultation fee, and specialty match, which helps patients pick care they can afford. Next, the patient can meet the recommended doctor in a live video consultation delivered by an adaptive, low-bandwidth video engine that supports multiple languages. When the visit ends, a digital e-prescription is issued, and the patient can look up real-time medicine stock at nearby partner pharmacies before setting out to collect the medicines. The admin interface allows platform staff to verify doctors and hospitals, manage pharmacy stock records, and monitor overall usage. The platform is a lightweight web application built on a Flask/Node.js-style backend, a trained symptom-classification model, and a shared relational database. The platform shows that a software-only approach with minimal infrastructure can meaningfully improve access, affordability, and language inclusivity in rural healthcare, with no need to deploy specialized hardware.