• G.S.S.S.S.V.KRISHNA MOHAN
• Karasu sarvani
• kalivarapu Avinash
• Dubba Harathi
• Yelagada Pavan Kumar

The implementation of smart healthcare technologies gained increased importance for early detection because it allows for immediate response in recent years. This paper presents the development process and design strategy of the Intelligent Health Tracking System through Internet of Things (IoT) along with predictive analytics which tracks vital signs to detect potential emergencies. A Raspberry Pi 3 Model A+ functions as the system controller while it communicates with an MPU6050 accelerometer for motion detection and a DS18B20 digital temperature sensor as well as a MAX30102 sensor which monitors heart rate and SpO₂ levels. Feedbacks emerge instantly through the 16x2 LCD screen and in crisis situations the buzzer produces a warning signal. Sensing data flows to the Adafruit IO cloud platform where the information supports both monitoring operations and visualization functions. Analysis of sensor data through K-Nearest Neighbors (K-NN) machine learning model enables correct prediction of health issues. The proposed system represents a functional cost-effective solution for medical pre-emptive care because it unifies predictive functions with direct observation methods. System experimental data supports vital sign anomaly detection ability that leads to decreased delays in emergency medical responses. Future healthcare systems will gain greater mind-power capabilities because of this research thus significantly supporting chronically ill and elderly patients

Healthcare management| Internet of Things (IoT)| K-Nearest Neighbors (K-NN)| Predictive Analytics| Remote Monitoring

"INTELLIGENT HEALTH TRACKING SYSTEM FOR EMERGENCY DETECTION EMPLOYING IOT AND PREDICTIVE ANALYTICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.l659-l663, April-2025, Available :http://www.jetir.org/papers/JETIR2504B82.pdf

"INTELLIGENT HEALTH TRACKING SYSTEM FOR EMERGENCY DETECTION EMPLOYING IOT AND PREDICTIVE ANALYTICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppl659-l663, April-2025, Available at : http://www.jetir.org/papers/JETIR2504B82.pdf