Table 1 Comparative analysis of the existing state of the art.

Gupta et al.⁵⁵

Y

N

N

N

N

N

Y

Y

Y

Y

Blockchain enabled system for early classification and detection of monkey-pox with the help of transfer learning on skin lesion dataset

Increased latency and bandwidth while accessing blockchain

Akhtar et al.⁵⁶

Y

N

N

N

N

Y

Y

Y

Y

N

Internet of medical thing based healthcare monitoring system that uses improved advanced feature set RNN

System requires high bandwidth and require large space to store patients data that is not secure

Nancy et al.³⁷

Y

Y

Y

N

N

Y

N

N

N

Y

A healthcare monitoring system for remote monitoring of patients health and real-time analysis using IOT and Cloud

To handle IOT data requires higher bandwidth

Ahmed et al.³⁸

Y

Y

Y

N

Y

Y

Y

N

Y

Y

A Perceptual Encryption method, applicable for both the images i.e. color and grayscale, improves robustness against different attacks

An assumption of a cloud computation server that is private, which may not be applicable in all settings

Gupta et al.⁴⁰

Y

N

N

Y

Y

Y

Y

N

N

N

The hierarchical model integrates seamlessly with the healthcare network’s hierarchical structure

Increased risk of malicious agents stealing or altering sensitive patient data

Qamar et al.⁴¹

Y

N

N

N

N

N

Y

N

Y

Y

Utilizes DL-based classification and feature selection to analyze EHR data with a focus on cyber security

Additional complexity and potential security risks

Simeone et al.⁴²

Y

N

N

Y

Y

N

N

N

Y

Y

Cloud-based platform for worker health monitoring in hazardous manufacturing environments

The potential cost and complexity for implementation

Bolhasa-ni et al.⁵⁷

Y

N

N

Y

N

N

N

N

N

N

Comprehensive analysis of the possible uses of DL in IoT-based healthcare systems

Data Privacy and Security, increased risk of data breaches

Cotroneo et al.⁴⁴

Y

N

N

N

N

N

Y

Y

Y

Y

Yields comparable or superior results to manual clustering, which requires significant human effort and expertise

Requires high hardware requirements

Motwani et al.⁴⁵

Y

Y

N

N

N

Y

N

Y

Y

Y

Smart monitoring architecture monitors chronic patients in real-time and predicts Emergency, Alert, Warning, and Normal scenarios equally well locally and in the cloud

May require high costs for implementation and maintenance

Aazam et al.⁵⁸

Y

N

N

N

N

N

Y

N

Y

Y

Explored the use of ML in healthcare applications with edge computing

Challenges in ensuring interoperability between different devices and systems, which can limit the ability to scale and deploy such solutions on a larger scale

Hossain et al.⁴⁶

Y

Y

Y

Y

Y

Y

Y

N

Y

Y

Adequate for parallelization

Need for a reliable and high-speed internet connection

Praveen et al.⁵⁹

Y

Y

Y

N

N

Y

Y

N

Y

Y

OGSO-DNN is an energy-efficient illness detection and clustering approach for IoT-based sustainable healthcare systems

Scalability, Data privacy and security can be an issue

Shah et al.⁶⁰

Y

Y

N

Y

Y

Y

N

Y

Y

Y

Improves data accuracy and processing speed in IoT environments

Requires high bandwidth and robust infrastructure

Yan et al.⁵⁰

Y

N

N

N

N

N

Y

N

Y

Y

RSIF framework enhances healthcare data access in the cloud for users and service providers

May require a significant amount of computational resources

Tuli et al.⁵²

Y

N

N

Y

Y

Y

Y

Y

Y

Y

HealthFog: a portable, cost-effective solution for heart disease diagnosis using ensemble DL

Requires high compute resources for training and prediction

Durga et al.⁶¹

Y

N

N

N

N

N

N

N

N

N

Explored algorithms for enhancing IoT-based healthcare systems in this study

High Complexity and Computation time