High-Resolution Indoor Sensing Using Channel State Information of WiFi Networks
Round 1
Reviewer 1 Report
This work presents an interesting method for indoor sensing using available WiFi equipment. Channel state information (CSI) raw data can be extracted from physical layer and be processed. Outputs of the proposed technique are a set of accurate information on breathing rate, heartbeat and angle of arrival of the incoming signal. Proposed method, as authors claimed, benefits of “the same hardware with communication systems due to the congestion in the frequency spectrum”. Available public CSI data processing steps is well presented through paragraphs of Section 3.1. Results presented in figures 11, 12 and 13 demonstrate the effectiveness and the accuracy of proposed method. Applications of this work are crucial as authors said :” This is particularly important for applications in search and rescue, healthcare, and security”
English writing style is perfect and I enjoyed myself when I was reading this paper
I think this work is a real contribution in the indoor sensing techniques using WiFi hardware, and it deserves to be published in its actual from
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
page 14 has "Figure ??." Which should be corrected
The article has a section on "results and discussion". However, it fails to discuss the results within the context of literature.
Quality of english is fine
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
1. Some recent related works need to be added for review and comparison, such as
[1] Q. Huang, et al., "Refining Wi-Fi based indoor localization with Li-Fi assisted model calibration in smart buildings," 16th International Conference on Computing in Civil and Building Engineering, pp. 1358-1365, 2016.
[2] Hernández N, Ocaña M, Alonso J M, et al. Continuous space estimation: Increasing WiFi-based indoor localization resolution without increasing the site-survey effort[J]. Sensors, 2017, 17(1): 147.
[3] Chen J, Ou G, Peng A, et al. An INS/WiFi indoor localization system based on the Weighted Least Squares[J]. Sensors, 2018, 18(5): 1458.
[4] Tuta J, Juric M B. A self-adaptive model-based Wi-Fi indoor localization method[J]. Sensors, 2016, 16(12): 2074.
2. The authors only describe their own algorithms and experimental results. I think you should also compare your results with other existing works in the literature. Please add a section to comprehensively compare and discuss the advantages and disadvantages between your work and other works.
acceptable
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Discussion section has been added. However the authors should avoid the use of "we" in the sentences.
This work needs proof reading.
Author Response
Thanks for your review. We have revised the discussion section, and uses of "we" have been avoided. Even though we believe that the use of "I" in an academic paper should be avoided, but the use of "we" should be acceptable. But we agree with the reviewer that the number of appearances should be reduced. The minor updates have been marked as red. We also ask a native English speaker to read this manuscript again. Thank you.
Reviewer 3 Report
Thanks for your efforts. The quality of this work has been improved.
Author Response
Appreciated your comments. We have tried our best to improve the quality of the paper and thank you for your recognition. We have checked through all references and reaffirmed their relevance to this work.
