Revolutionizing Patient Care with AI and Cloud Computing: A Framework for Scalable and Predictive Healthcare Solutions

Hara Krishna Reddy Koppolu, Mahesh Recharla, Chaitran Chakilam

Abstract: The demand for smart healthcare systems is dramatically increasing due to the growing variety of high-tech and intelligent devices supporting health monitoring and data gathering. Wearable devices such as Fitbits, smartwatches, and blood pressure monitors are examples of the current wearable technology. Furthermore, the term smart home refers to homes equipped with smart devices capable of automatically collecting and forwarding patient data to hospitals. Examples of smart home devices include blood oxygen monitors, body temperature sensors, and glucose meters. The emergence of smart healthcare systems aids elderly people in living independently while 24/7 monitoring their health status as well as detection of critical events in smart homes. Moreover, the COVID-19 pandemic highlighted the necessity, potential, and importance of smart healthcare services and systems. Most medical devices and tools appeared several decades ago and are expensive. There is an increasing demand for affordable and effective smart healthcare services for all patients. Three main obstacles exist in utilizing intelligent healthcare services. First, current connected devices and sensors have limited ability for real-time analytics, detecting critical events, and performing quick actions, because their edge devices cannot be smart enough. Second, wearable devices and smart homes generate an enormous volume of continuous data that exceeds the storage and processing capability of cloud servers. Besides, moving all data to the cloud consumes a lot of energy and time and exhausts network bandwidth. Third, captured data in a smart environment must be stored and processed for a long time to have value, while health data is usually sensitive and must be stored and processed privately . On the other hand, patient safety and in-time treatment are paramount in smart healthcare systems and for the related infrastructures, less time consumption in decision making is also critical. There should be intelligent methods to convert the raw data into intent, derive rules from them, and warn patients as soon as an abnormal behavior is detected.

Keywords: AI in Patient Care, Cloud-Based Healthcare, Predictive Analytics, Scalable Health Solutions, Digital Health Innovation, Healthcare Cloud Infrastructure, Real-Time Health Insights, Clinical Decision Support Systems (CDSS), Remote Health Monitoring, AI-Powered Diagnostics, Health Data Interoperability, Virtual Care Platforms, Patient Outcome Optimization, Intelligent Health Systems, Healthcare Automation

How to Cite?: Hara Krishna Reddy Koppolu, Mahesh Recharla, Chaitran Chakilam, "Revolutionizing Patient Care with AI and Cloud Computing: A Framework for Scalable and Predictive Healthcare Solutions", Volume 11 Issue 12, December 2022, International Journal of Science and Research (IJSR), Pages: 1457-1472, https://www.ijsr.net/getabstract.php?paperid=MS2212142204, DOI: https://dx.doi.org/10.21275/MS2212142204