MediBot: IoT-Driven Healthcare for Remote Communities
It is a new IoT-included healthcare application for remote supervision of patients’ health overseeing signs and notifying in case of detecting possible health issues with the help of advanced sensor technology. Plan C: MediBot to use sensors to take measurements of remote patients' body temperature, pulse, SpO2, movements, and environment; MediBot acquires real-time health data, with data displayed at the local level as well as in the cloud through an ESP32 microcontroller. This allows users to remotely choose, recommend their vitals, and schedule appointments with healthcare providers using MediBot based on specialists, the latter can monitor in real-time patient-shared vitals and data and may prescribe drugs online. Using live data classification, MediBot accurately identifies potential health deteriorations such as fever, hypoxia, stress, sleep apnea, and dehydration and opportunities for medical interference. The subset connects the patient and doctor by closing the loop and continued screening so that the availability and effectiveness of services are improved. MediBot is a smart healthcare system applied to IoT with the help of sensors and machine learning to predict the health state of patients. Real-time physiological indices such as body temperature, pulse rate, blood oxygen saturation, movement, and environmental conditions are captured through sensors mounted on MediBot and presented on a local interface as well as the ESP32 microcontroller uploading data to the cloud. Using al; machine learning algorithms, MediBot in real-time and historical data to assess health risks such as fever, hypoxia, stress, sleep apnea, and dehydration, allowing for timely alerts for the patient’s immediate medical attention. Thus it creates a channel of constant supervision, and preliminary and effective interaction as well as improves the organization and effectiveness of managing the patients’ and doctors’ encounters.
Authors
- D Nandhini
- J Ramprabu
Publication Details
- Published
- 2025-04-04
- DOI
- https://doi.org/10.1109/icaeca63854.2025.11012279
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00