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Advanced Analytics for Disease Tracking & Remote Intravenous Injection Monitoring

Darwin S.*, Thanapriya B.**, Sowmiya S.***, Sowmiya N.****, Malini P.*****

*-***** Department of Electronics and Communication Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, Tamil Nadu, India.

Periodicity:January - June'2024
DOI : https://doi.org/10.26634/jcc.11.1.20801

Abstract

This system is proposed to address the challenges healthcare professionals face in monitoring patients who require intravenous infusion. This treatment method is commonly used for patients with dehydration, malnutrition, or those unable to take oral medications. The system enables remote monitoring of a patient's health and reduces the workload of healthcare professionals. The process begins with a doctor prescribing the necessary dose of drip bottles, which are then configured by the nurse accordingly. Once set for automatic operation, the system diligently calculates and monitors the fluid level and infusion rate using a load cell sensor. Additionally, the patient's vital signs, including heart rate, body temperature, and oxygen levels, are continuously monitored and stored in a database using cloud computing technology, enabling robust data analysis. The system provides real-time feedback on infusion parameters through an LCD screen. In the event of a patient's health deteriorating below a threshold level, a message is sent to the doctor, accompanied by a buzzer sounding and a red LED flashing at the patient's bedside. A supervisor continuously monitors the patient's health report, promptly informing the physician of any rapid changes and facilitating immediate treatment. This comprehensive system enhances patient care, streamlines medical monitoring processes, and enables swift responses to emergent health situations.

Keywords

Intravenous (IV) Infusion, Patient's Vitals, Data Analytics, Database, Alert System, Remote Monitoring, Cloud Computing.

How to Cite this Article?

Darwin, S., Thanapriya, B., Sowmiya, S., Sowmiya, N. and Malini, P. (2024). Advanced Analytics for Disease Tracking & Remote Intravenous Injection Monitoring. i-manager's Journal on Cloud Computing, 11(1), 20-29. https://doi.org/10.26634/jcc.11.1.20801

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