Leveraging Cloud Computing for Real-Time Big Data Analytics in Healthcare Systems

Samadhan Bundhe; Swayam Shashank Shah; Radha Thorat; Rutuja More; Anand Singh Rajawat; Ram Kumar Solanki

doi:10.57159/jcmm.4.6.25202

Authors

Samadhan Bundhe
Swayam Shashank Shah JSPM'S Jayawantrao Sawant College of Engineering, Pune, India
Radha Thorat JSPM'S Jayawantrao Sawant College of Engineering, Pune, India
Rutuja More JSPM'S Jayawantrao Sawant College of Engineering, Pune, India
Anand Singh Rajawat School of Computer Science & Engineering, Sandip University, Nashik , India
Ram Kumar Solanki

DOI:

https://doi.org/10.57159/jcmm.4.6.25202

Keywords:

Cloud Computing, Big Data Analytics, Healthcare Systems, Real-Time Processing, Patient Care

Abstract

Electronic health records (EHRs), medical imaging, and wearable devices generate vast amounts of data in healthcare systems, necessitating scalable, real-time analytics. The proposed study recommends a cloud-based system that combines streaming ingestion and Apache Spark processing with machine learning-based predictive models and Gomoku-inspired stream-cipher encryption, along with blockchain validation. The proposed framework is designed to support continuous data ingestion, low-latency processing, and secure analytics in distributed healthcare environments. Experimental evaluation demonstrates that the system achieves a 96.5% F1-score, 120 ms processing time, 450 MB/s throughput, and 68% resource usage, outperforming Hadoop (90.2% F1-score, 350 ms) and Spark (94.1%, 200 ms) in processing latency, throughput, and resource efficiency. Findings further indicate that operational costs would be reduced by 30%, early intervention rates would improve by 85%, and patient engagement would increase by 40%, enabling the delivery of proactive and personalized healthcare. Additionally, integrating game-theoretic key generation with cloud-based analytics enhances data confidentiality and integrity for real-time healthcare applications. The proposed approach demonstrates the feasibility of combining scalable cloud computing, real-time big data analytics, and advanced security mechanisms to address the growing demands of modern healthcare systems.

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