Design and Application Research of a UAV-Based Road Illuminance Measurement System

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents the development of an innovative system that uses Unmanned Aerial Vehicles to measure road lighting. Utilizing a HUBSAN Zino 2+ UAV equipped with sensors and GPS, the system collects and transmits data to a cloud platform for real-time analysis. This method significantly improves efficiency and safety compared to traditional manual measurements, with a low error rate in illuminance readings. The research demonstrates the system's ability to create detailed lighting distribution maps, enhancing the evaluation of road lighting quality and suggesting broader applications for improving road safety and design.

The authors use innovative approach to measuring road illuminance using UAVs. The system they have developed offers significant improvements in terms of efficiency, safety, and data accuracy compared to traditional methods. The detailed explanation of the hardware and software components, as well as the experimental results, provide a clear understanding of the system's capabilities and potential applications.

However, I have a few suggestions for minor revisions to enhance the paper:

1.) Expand the Literature Review (to at least 50 references): While the current literature review is adequate, it would benefit from a more comprehensive discussion of related work. Specifically, the authors could include additional studies on UAV applications in similar fields, recent advancements in sensor technologies for illuminance measurement, and comparisons with other automated measurement systems.

2.) Improve Figure Quality: Some of the figures, particularly Figure 4 and Figure 8, need higher quality to improve readability. Enhancing the resolution and clarity of these images would make the visual information more accessible to readers.

Overall, I find the paper to be a valuable contribution to the field.

Comments on the Quality of English Language

The quality of English language in the manuscript is good, but I recommend minor editing to address some lengthy and complicated sentences that are hard to read.

 

Author Response

Comments 1: Expand the Literature Review (to at least 50 references): While the current literature review is adequate, it would benefit from a more comprehensive discussion of related work. Specifically, the authors could include additional studies on UAV applications in similar fields, recent advancements in sensor technologies for illuminance measurement, and comparisons with other automated measurement systems.

Response 1:

Thank you for your suggestion. I have expanded the introduction section by adding over ten additional studies on the application of drones in related fields, as well as literature on automated illuminance measurement, and provided a comprehensive discussion of these works. This expanded content can be found on pages two and three of the manuscript, from lines 45 to 122. Additionally, the total number of references in the manuscript has increased to 51, ensuring broader coverage of relevant research.

Comments 2: Improve Figure Quality: Some of the figures, particularly Figure 4 and Figure 8, need higher quality to improve readability. Enhancing the resolution and clarity of these images would make the visual information more accessible to readers.

Response 2:

Thank you for pointing out this issue. I have updated all the images from Figure 1 to Figure 8 throughout the manuscript. The new images have higher resolution and clarity, enabling readers to more easily obtain visual information.

Reviewer 2 Report

Comments and Suggestions for Authors

This paper aims a UAV-based system for measuring road illumination and to evaluate its performance through a series of experiments.

Their contributions are presented as a new UAV-based road Illumination measurement system as hardware and software, to ensure safety during measurements by allowing UAV control and monitoring from the roadside, and to create an illuminance distribution map.


There are no recent references. It seems like a perfect hardware design and UAV-based road Illumination measurement system. However the given references are not fair. For example, ref 10 is about image processing detecting road defects using images. It is not directly related to the topic of this paper. The contribution to the literature is not clear. The paper doesn't give a comparative contribution in the introduction.

The paper doesn't have technical errors. However, the topic is not up-to-date. It does not attract the interest of the reader. There is no autonomous mapping or novelty.

Author Response

Comments 1: There are no recent references. It seems like a perfect hardware design and UAV-based road Illumination measurement system. However the given references are not fair. For example, ref 10 is about image processing detecting road defects using images. It is not directly related to the topic of this paper. The contribution to the literature is not clear. The paper doesn't give a comparative contribution in the introduction.

Response 1:

Thank you for your detailed review and valuable feedback on our work. In response to your comments, we have made the following improvements:

1.Updated References: We have added several recent references to ensure the cited literature is more comprehensive and up-to-date. These new references cover the application of drones in road lighting measurement and related design aspects, enhancing the timeliness and relevance of our paper.

2.Corrected Irrelevant Citations: We carefully reviewed all references and removed those not directly related to the topic of our paper. For instance, Reference 10, which discussed image detection of road defects, has been replaced with more relevant literature.

3.Clarified Literature Contributions: In the introduction section, we reorganized the discussion of existing literature, clearly stating the contributions of each reference and their relevance to our research.

These revisions can be found on pages two and three of the manuscript, from lines 45 to 99.

 

Comments 2: The paper doesn't have technical errors. However, the topic is not up-to-date. It does not attract the interest of the reader. There is no autonomous mapping or novelty.

Response 2:

Thank you for your feedback. In response, we have made the following improvements:

1. Updated References: In the introduction section, we have updated the references to include the latest research, particularly on drone technology and road lighting measurement. This demonstrates the close alignment of our study with current technological trends.
2. Detailed Explanation of Research Contributions and Innovations: In the introduction and discussion sections, we have detailed the contributions and innovations of our research, clearly showcasing our study's unique contributions and improvements.
3. Practical Application and Data Analysis: The paper includes extensive practical application and data analysis, illustrating the system's performance in road environments.

These improvements are detailed on page 3, lines 100 to 122, and page 24, lines 684 to 716.

We believe these enhancements will further increase the academic value and appeal of the paper.

Reviewer 3 Report

Comments and Suggestions for Authors

This paper presents a UAV-type path measurement system and evaluates its performance through research. The system uses a UAV, a microcontroller, a sensor, GPS and integrates flight, processing, measurement, cloud network, obstacle avoidance, communication and power components through the Opened platform. Both hardware and software are implemented using the Z-Score algorithm to resolve outliers in exposure data. The system showed a single measurement error of 1.14% and a MAPE of 5. 08% for most rates. In the experiment, the horizontal and vertical illumination values of the system were RMSE 1.92 lx and 1.75 lx. Authors claim a real-time interface will increase operational efficiency, cut labor costs in half and cut time by approximately four-fifths. Flight control and direct control from the road ensured safety during testing.  This resulted in the creation of both horizontal and vertical maps of the illuminated plane. The findings provide valuable information for assessing the quality of street lighting, increasing road safety and improving road design.

The necessary corrections to be made in the article are as follows:

1. Literature review should be expanded.

Feroz, S., & Abu Dabous, S. (2021). Uav-based remote sensing applications for bridge condition assessment. Remote Sensing, 13(9), 1809.

Unal, G. (2021). Visual target detection and tracking based on Kalman filter. Journal of Aeronautics and Space Technologies, 14(2), 251-259.

Outay, F., Mengash, H. A., & Adnan, M. (2020). Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges. Transportation research part A: policy and practice, 141, 116-129.

Vaaja, M. T., Maksimainen, M., Kurkela, M., Virtanen, J. P., Rantanen, T., & Hyyppä, H. (2020). Approaches for mapping night-time road environment lighting conditions. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 5(1), 199-205.

Hossain, M., Hossain, M. A., & Sunny, F. A. (2019). A UAV-based traffic monitoring system for smart cities. In 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI) (pp. 1-6). IEEE.

Wu, X., Shen, X., Cao, L., Wang, G., & Cao, F. (2019). Assessment of individual tree detection and canopy cover estimation using unmanned aerial vehicle based light detection and ranging (UAV-LiDAR) data in planted forests. Remote Sensing, 11(8), 908.

Kiyak, E., Gol, G., & Karakoc, T. H. (2017). Obstacle detection and collision avoidance using indoor quadrocopter. International Journal of Sustainable Aviation, 3(4), 297-311.

2. Some figures extend beyond the page and should be reduced: 2 and 6.

3. How long is the flight duration in the experimental setup? How many meters can the experimental setup be carried out for?

 

4. According to what reference was the reduction in labor and time costs made? It should be explained.

Author Response

Comments 1:  Literature review should be expanded.

Feroz, S., & Abu Dabous, S. (2021). Uav-based remote sensing applications for bridge condition assessment. Remote Sensing, 13(9), 1809.

Unal, G. (2021). Visual target detection and tracking based on Kalman filter. Journal of Aeronautics and Space Technologies, 14(2), 251-259.

Outay, F., Mengash, H. A., & Adnan, M. (2020). Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges. Transportation research part A: policy and practice, 141, 116-129.

Vaaja, M. T., Maksimainen, M., Kurkela, M., Virtanen, J. P., Rantanen, T., & Hyyppä, H. (2020). Approaches for mapping night-time road environment lighting conditions. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 5(1), 199-205.

Hossain, M., Hossain, M. A., & Sunny, F. A. (2019). A UAV-based traffic monitoring system for smart cities. In 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI) (pp. 1-6). IEEE.

Wu, X., Shen, X., Cao, L., Wang, G., & Cao, F. (2019). Assessment of individual tree detection and canopy cover estimation using unmanned aerial vehicle based light detection and ranging (UAV-LiDAR) data in planted forests. Remote Sensing, 11(8), 908.

Kiyak, E., Gol, G., & Karakoc, T. H. (2017). Obstacle detection and collision avoidance using indoor quadrocopter. International Journal of Sustainable Aviation, 3(4), 297-311.

Response 1:

Thank you for your valuable feedback on the first point. We have expanded the literature review and incorporated six of the seven references you mentioned into the review section, with the remaining reference added to the subsequent references section of the paper. The revised introduction includes over ten new studies on the application of drones in related fields, as well as literature on automated illuminance measurement, and provides a comprehensive discussion of these works. This updated content is located on pages two and three of the manuscript, from lines 45 to 122.

 

Comments 2: Some figures extend beyond the page and should be reduced: 2 and 6.

Response 2: Thank you for your feedback on this point. I have revised Figures 2 and 6 to ensure they fit within the page limits.

 

Comments 3: How long is the flight duration in the experimental setup? How many meters can the experimental setup be carried out for?.

Response 3:

Thank you for highlighting this point. The experimental device has a single flight time of 34 minutes, which can be extended by carrying multiple spare batteries. The device's WIFI coverage range is 100 meters, which means the data transmission distance is also 100 meters. If the test personnel stand in the center of the test area, they can measure the road space within approximately 200 meters in both directions. This explanation is provided on pages 10 to 11, lines 324 to 329, and page 15, lines 471 to 481 of the manuscript.

 

Comments 4: According to what reference was the reduction in labor and time costs made? It should be explained.

Response 4:

Thank you for raising this point. The basis for reducing labor and time costs in this study is derived from a comparison with traditional manual measurement methods. In our experiment, traditional manual measurement requires two people working together for 40 minutes to complete the measurement. In contrast, our system requires only two people working together for 8 minutes. Therefore, it saves 1/2 of the labor cost and 4/5 of the time cost. This explanation is provided in detail on page 10, lines 450 to 453 of the manuscript, and further discussed in the discussion section.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

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