Revolution in Healthcare Monitoring: Merging Machine Learning with Wearable and Wireless Technologies for Holistic Patient Care
Sensors and wireless communication with machine learning to provide realtime patient monitoring and analysis. Using a Raspberry Pi as the central controller, the system collects data from a heartbeat sensor, temperature sensor, respiratory sensor, and MEMS sensor. An ADC module ensures accurate signal conversion, while an LCD displays vital information. a buzzer provides immediate warnings in critical conditions. The Random Forest machine learning algorithm analyzes sensor data to detect abnormalities and improve predictive healthcare. This system enhances patient care by offering continuous monitoring, early anomaly detection, and automated alerts, making it ideal for applications
Institutions
- Dr. NTR University of Health Sciences (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-06-30
- DOI
- https://doi.org/10.5281/zenodo.15770258
- Primary Topic
- Microbial bioremediation and biosurfactants
- Type
- article
- Field-Weighted Citation Impact
- 0.00