Table 3. Key challenges and proposed solutions for fog computing in healthcare.

AI: artificial intelligence; ML: machine learning.

Challenge	Description	Proposed solutions
Interoperability	Difficulty in seamless integration of diverse medical devices and systems	Development and enforcement of universal standards for device communication and data formats
Scalability	Need to handle growing data volumes and device connectivity without performance degradation	Enhance local processing power and develop scalable network architectures
Security	High risk of data breaches and unauthorized access due to decentralized data processing	Implement advanced encryption, use blockchain technology for secure data transactions, and continuous security monitoring
Technical limitations	Limitations in local computational power, especially in remote or resource-limited healthcare settings	Deploy AI and ML to optimize data processing efficiency and manage computational loads
Maintenance	Managing and updating numerous decentralized nodes can be complex and resource-intensive	Utilize sophisticated management tools and skilled personnel, automate updates and maintenance routines