Iot- Powered Autonomous Healthcare and Telemedicine Framewor

Abstract

Introduction: As experienced specialists, meetings will economize time and exertion, particularly for the provincial individuals, since most of the experienced specialists more often than not do well in urban ranges.

Objectives: The proposed IoMT-based system uses sensors (DHT11, MAX30100) to monitor patient vitals and enables doctor consultation via video call, with data sent through ESP8266 and Wi-Fi. After consultation, medicines are dispatched using a motor-controlled AMM unit and all health data is securely stored on the cloud. The system supports remote care and diagnosis for all users, including the elderly and disabled.

Methods: The simulation used Arduino as the core with sensors like LM35 (temperature), MAX30100 (pulse & SpO2), and respiratory sensors, displaying real-time vitals on a 16x2 LCD. Data was wirelessly transmitted via ESP8266 to support telemonitoring and cloud storage. The system also included a motor-controlled drug dispatch unit, simulated using engine drivers. It operated efficiently under solar-powered conditions, ensuring usability in remote areas. Real-time alerts were triggered during critical health events. The system demonstrated reliable monitoring and responsiveness in rural healthcare settings. Proteus simulation confirmed successful integration and functioning of all modules.

Results: The project successfully achieved its goal of creating an IoT-based medical platform (AMM) for rural healthcare, integrating video consultation and automated medicine dispensing. It features real-time monitoring of vitals like temperature (40°C), heart rate (46 BPM), SpO2, and respiration rate (15) using sensors. Data is transmitted via Wi-Fi and displayed on an LCD, with alerts for critical health events. The system is solar-power compatible, ensuring usability in remote areas. A user-friendly design and low complexity make it accessible. It also aims to set a standard framework for future IoT medical applications. Simulation results confirm accurate and efficient performance.

ConclusionsThe proposed IoT-based medical system effectively enables remote health monitoring and automated medicine dispensing, especially for rural areas. It ensures real-time data transmission and accurate vital tracking using integrated sensors. The system operates reliably even in low-resource settings with solar power support. Overall, it offers a scalable, user-friendly solution for improving healthcare accessibility.