Table 1.
Comparative analysis of the existing state of the art.
| References | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Pros | Cons |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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 |
1-Accuracy, 2-Sensitivity, 3-Specificity, 4-Latency, 5-Bandwidth Utilization, 6-Robustness, 7-Security, 8-Fault Tolerant, 9-Efficiency, 10-Reliability.