Table 6.

Massive data challenges with Healthcare 4.0.

Challenge	Issues with Healthcare 4.0
Data volume	Healthcare 4.0 generates vast volumes of data from massive deployed medical devices. Managing and processing such large datasets can strain existing storage and computing resources.
Data diversity	Healthcare data comes in various formats, including structured data (e.g., EHRs), unstructured data (e.g., medical imaging), and streaming data from IoMT devices. Integrating and analyzing this diverse data is complex and requires advanced data processing techniques.
Data generation rate	The speed at which data is generated and needs to be processed in real-time can pose traditional data processing systems. Real-time analysis is critical for immediate clinical decisions and timely interventions.
Data analytics and insights	Extracting meaningful insights from large and complex healthcare datasets requires sophisticated data analytics tools and expertise. Analyzing data effectively can be resource-intensive and time-consuming.
Data storing and archiving	Storing and managing historical healthcare data can be challenging due to its volume and the need for long-term retention for research, legal, and compliance purposes.