Enabling Pandemic-Resilient Healthcare: Edge-Computing-Assisted Real-Time Elderly Caring Monitoring System
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors1. It is suggested that the introduction should more clearly address the challenges facing the current care of the elderly, especially in relation to the urgent need for tele-care systems in the current social context, and the shortcomings of existing systems, so as to more clearly position the contribution of this study.
2. The literature review section could be further expanded to include more recent research findings on edge computing, software-defined networking (SDN), and mobile edge computing (MEC) in telemedicine and elder care to enhance the theoretical basis of the research.
3 The system architecture diagrams in Figures 1 and 2 can be further refined to clarify the data flow and control flow between the individual components and how they work together to enable real-time remote care.
4When describing the LSTM model, more details about the model training process, hyperparameter Settings, and model evaluation metrics (such as accuracy, recall, etc.) can be added so that readers can better understand and reproduce the experimental results.
5 The data set, simulation environment, parameter Settings, etc. used in the experiment should be detailed so that other researchers can repeat the experiment and verify the results.
6 The results can be further analyzed, for example, the influence of different parameter Settings on system performance, as well as the stability and reliability of the system under different network conditions.
7 In the discussion section, the comparison with the existing tele-care system can be increased to highlight the innovation and advantages of this study.
8 The last part of the paper can clearly list the direction of future work, such as further optimization of system architecture, improvement of model prediction accuracy, expansion of system functions, etc.
9 Some of the expressions in the article are rather lengthy, and it is suggested to refine them in order to improve the readability of the article.
10 Ensure that the reference list includes the latest relevant research results to reflect the current and cutting-edge research.
Comments on the Quality of English Language9 Some of the expressions in the article are rather lengthy, and it is suggested to refine them in order to improve the readability of the article.
10 Ensure that the reference list includes the latest relevant research results to reflect the current and cutting-edge research.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe authors presents an Edge Computational Intelligence (ECI) based haptic-driven elder telecaring system for remote caring and monitoring of elderly people. It utilizes software-defined network (SDN) and Mobile Edge Computing (MEC) to reduce latency and enhance responsiveness. Dual Long-term Short Memory (LSTM) models are deployed at the edge to enable location-aware real-time activity prediction to ensure QoS and QoE. The results from the simulation demonstrate that the proposed system is proficient in managing the transmission of data in real-time data without and with activity recognition and location-aware model by communication latency under 2.5 ms (more than 60%) and from 11∼12 13 ms (60%∼95%) for data packets 10 to 1000, respectively. Here some comments:
1. "The proposed system serves as a testbed for implementing, investigating, 16 and managing elder telecaring services for QoS/QoE provisioning" Is possible to compare this testbed with others?
2. In figure 5, 6, etc. split (a), (b) etc.
Comments on the Quality of English LanguageNo comments.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for Authorsno more comments
