P Sudheer

Work place: Department of CSE (AI&ML) - CVR college of Engineering-Hyderabad-India-501512

E-mail: sudheerchanty7@gmail.com

Website:

Research Interests: Machine Learning, Deep Learning, Image Processing

Biography

SUDHEER PILLI obtained his B.Tech. Degree in Computer Science & Engineering from Jawaharlal Nehru Technological University, Kakinada, India in 2011. He further pursued his M.Tech in Computer Science & Engineering from the same university in 2014. Currently, pursuing a PhD. in Computer Science & Engineering. Presently, holds the position of Assistant Professor at the Department of Computer Science & Engineering in CVR College of Engineering, affiliated with Jawaharlal Nehru Technological University, India. His academic focus centers around Deep learning, Machine learning, NLP, Image processing reflecting his research interests. For any inquiries, he can be reached via email at sudheerchanty7@gmail.com

Author Articles
An Overview of Remote Patient Monitoring For Improved Patient Care and Cost Reduction: The Iot Revolutionizing Health Care

By Ravikumar Ch P Sudheer P Dharmendra Kumar

DOI: https://doi.org/10.5815/ijeme.2023.06.04, Pub. Date: 8 Dec. 2023

Modern technologies like 5G, the Internet of Things (IoT), and Artificial Intelligence (AI) have just come together, creating previously unheard-of chances for creative solutions. As a result, several IoT use cases have come to fruition, particularly in the healthcare industry, enabling the creation of eHealth and mHealth applications for ambient assisted living (AAL). However, there are practical issues with the current healthcare system, such as service delays and exorbitant expenses, which have had serious repercussions, such the untimely passing of famous people from heart attacks. Real-time patient monitoring and therapy with few delays are necessary to solve these pressing challenges. IoT has changed the game in this area by making it easier to establish Remote Patient Monitoring (RPM) systems. Vital indicators can be sent in real time to clinicians using IoT-enabled wearable devices (biosensors), enabling quick intervention and the start of treatment. This article gives an overview of the state-of-the-art in RPM using IoT, highlighting its potential to save time, lower healthcare expenses, and considerably raise patient quality of life and the caliber of healthcare services. It also identifies research holes and ways to use RPM systems, laying the groundwork for further development in this area.

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