Advancing ESG and SDGs Goal 11: Enhanced YOLOv7-Based UAV Detection for Sustainable Transportation in Cities and Communities

Round 1

Reviewer 1 Report

1.      This paper presents an extended object detection approach for UAV images. This work should focus on the main subject and remove all unnecessary and general topics.

2.      The abstract is too long with many redundancies. It should focus on the problem, novelty, and compared results.

3.      Figure 1 is close to a philosophic drawing and high-level architecture of an ideal world regarding ESG and SDGs. Could it specially and technically be concentrated on this paper’s subject?

4.      The terms like “channel attention mechanism” should be defined and cited in their references.

5.      The system model and proposed approach should have more detailed information with an enhanced presentation. Separation is required between the past studies and novelty in section 2. Materials and Methods.

6.      The time complexity of the proposed approach can be presented.

7.      All assumptions, restrictions, and also a discussion can be added.

 

8.      The experimental environment e.g. simulation, programming languages, libraries, etc. should be mentioned.

English is good and moderate editing is required.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

In this study, the authors modified the YOLOv7 E-ELAN model and loss function to make it more suitable for traffic scenarios and providing a comprehensive and effective strategy for achieving higher accuracy in YOLOv7-based unmanned aerial vehicles' detection systems. The paper is fluent, rich in content, and has strong theoretical significance, but its innovation is not clear, and the overall reading lacks novelty. The paper has the potential to be accepted for publication. Before that, the authors are advised to consider the following comments and suggestions. Therefore, I recommend a major revision for this submission.

1.     The title of the manuscript covers ESG and SDGs Goal 11, among other things, and the manuscript is about improving a class of algorithms or models, which is not very relevant to what is covered in the title. The authors should tell a clear story about how ESG and SDGs Goal 11 are intrinsically linked to drone detection and how it contributes to sustainable transportation in cities and communities.

2.     The abstract of the manuscript is overloaded with content and the authors are advised to condense the abstract to highlight the research focus of the paper.

3.     The introduction section should list studies related to drone detection and the promotion of sustainable transportation in cities and communities, and needs to identify the innovations of the research in this manuscript.

4.     The formulation of the SIoU should be exhaustive.

5.     In the results section, it is recommended to add information about the experimental environment, training parameter settings, etc.

6.     The conclusion section of the manuscript should be improved and enhanced to provide a detailed explanation of the research in this manuscript.

Author Response

"Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Appreciate the authors for enhancing the YOLOv7 model and improving its detection performance in UAV applications to promote sustainable transport. UAV is the future /current technology where much research is explored. The authors have identified the right topic, and I appreciate their efforts.

Overall, the manuscript is good. I have several comments as follows:

1. Section 1. Introduction: Additional writing is needed in Section 1 to clarify the novelty and contribution of the study compared to other studies.

2. The Abstract section is too lengthy and must be improved

3. Results are well written but need some statistical analysis. 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 4 Report

This study focused on enhancing the YOLOv7 method to improve the detection accuracy of especially small objects by using UAV which can be used as a part of more sustainable transportation. The article is well prepared and organized. However, the article seems to be like a technical report rather than a scientific paper since there is less in depth technical discussion of findings in "Results" section. The proposed method is well defined in Section 2, but in Section 3, it should be evaluated based on both findings and existing literature.

The article can be accepted based on the improvements in Section 3. Besides, there should be two small corrections in the article. Whenever an abbreviation is used in its first time in the article, the full length explanation of it should be given. Please use "unmanned aerial vehicles (UAV)" in line 33 instead of just using "UAV" and, "convolutional block attention module (CBAM)" in line 219 instead of just using "CBAM.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

All of my earlier comments have been effectively handled in this revised manuscript, and the study's quality in general has risen significantly. 

Author Response

Dear Reviewer:
Thank you to the reviewer  for your suggestions and approval.