Design and Implementation of A Real-Time Health Monitoring System Using IoT Sensors and Machine Learning Algorithms
Real-Time wi-fi Monitoring System Design & Implementation with IoT Sensors and System Learning Algorithms for Clinical Improvement - The motive is to decorate the healthcare enterprise with an advanced era. It collects patients’ we-fitness parameters like heartbeat, blood pressure, and body temp in real time with sensors of Net of things (IoT). The accumulated records are then despatched to a cloud server for addition processing and evaluation of the usage of the system gaining knowledge of algorithms. The system provides a user-friendly interface for healthcare professionals to receive the data and monitor patients remotely. It also sends a real-time alert notification if an abnormal reading is detected so that corrective actions can be taken quickly and possibly prevent major wireless issues. The machine learning algorithms employed in the system will be able to learn from all the data gathered, resulting in personalized and precise we-fitness tracking. The device design is scalable and can easily fit into current healthcare systems. It also has stable security features to ensure the pirates and confidentiality of patient records. This machine has so much potential and if applied correctly, it could change the way healthcare operates affecting a lot more people around the globe wireless powerful healthcare services to them, Wi-Fi -ally in remote & served parts of our planet. universal, Wifi-enabled tracking system in real-time has the potential to significantly improve patient outcomes and reduce healthcare costs.
Authors
- Anurag Aeron (ORCID: https://orcid.org/0000-0001-5636-9489)
- Sakil Ansari (ORCID: https://orcid.org/0009-0002-1606-9929)
- Pawan Kumar Goel (ORCID: https://orcid.org/0000-0003-3601-102X)
- Komal
- Vyom Sharma
Publication Details
- Published
- 2024-09-18
- DOI
- https://doi.org/10.1109/ic3i61595.2024.10829352
- Primary Topic
- Technology and Data Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00