Offline System for 2D Indoor Navigation Utilizing Advanced Data Structures

Round 1
Reviewer 1 Report
Comments and Suggestions for Authors1. The A* algorithm was published in 1968, the Dijkstra algorithm was proposed in 1956, and the improved A* algorithm is widely used. Although the improved A* algorithm is superior to the .A* algorithm and Dijkstra's algorithm, it is not innovative.
2. There are many ways to improve the A* algorithm, please add to the paper a description of the improvement of the modified A* algorithm used in the paper compared to the A* algorithm.
3. The system can navigate offline, which requires the indoor map data to be saved locally and takes up more local memory.
4. Some general-purpose mapping software can perform similar functions, e.g. Google Maps can be used for 2D navigation indoors at train stations, explain your advantages over such general-purpose mapping applications.
5. 2D indoor navigation should involve localization and path planning, but in this paper, localization is not involved and only path planning is included. Please elaborate on how localization is implemented.
Author Response
Please, find enclosed a detailed response
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe work presented by the researchers regarding the comparison of three different models for route optimization is important and valuable. They have evaluated their work in terms of usability, efficiency, and user satisfaction. However, there are a few points that require clarification.
General Comments:
- The majority of the figures used are either unclear or contain text in a language other than English. It is recommended to update these figures for better clarity.
- In lines 246 and 248, the word "Internet" appears within the sentence but starts with a capital letter. Please correct this formatting inconsistency.
Other Comments:
- In line 133, it is stated that "the objective of this study is to show how graph theory and the A algorithm enable route planning optimization in complex indoor environments through an indoor navigation mobile application."* However, how was this measured in the study? Please provide clarification.
- In line 186, regarding the Satisfaction Questionnaire, it is important to explain how the participants for the study were selected. Additionally, what was the rationale for selecting these two variables? Was there a reference from the literature to justify their selection, or were they self-defined?
- In line 208, it is mentioned that this study provides a more accessible and practical alternative, particularly in areas with limited infrastructure. How does the study substantiate this claim?
- In line 233, the authors state that "the integration of graph theory in the mobile application enables efficient modeling of complex indoor environments as simplified nodes and edges, representing rooms, hallways, and navigation paths (Figure 8). This abstraction minimizes computational complexity and allows the application to process data rapidly, even on devices with limited resources." However, how is this claim supported by numerical evidence? To what extent does it reduce computational complexity compared to the other models?
- Although it is mentioned in line 345 that a matrix-based model was used, how does its memory usage compare to the other models on the mobile device where it was installed and tested?
- Figure 9 presents a comparison of the three models, but it would be helpful to include an optimization plot to illustrate the time taken by each model to find the optimal path compared to other algorithms. Additionally, the X-axis is labeled as "average execution time", while the Y-axis is labeled as "climbing time and length." Are both of these measurements related to time? If so, what is the unit of measurement—nanoseconds, seconds, or minutes? Please clarify.
- Since this study focuses on optimization techniques, it would be beneficial for the authors to present a Pareto chart for optimal paths to improve clarity and understanding.
- The authors are encouraged to provide the source code and data repository to facilitate the reproduction of results.
- It will be good to present some results based on the given dataset for indoor navigation.
It is ok, but it needs to address the grammatical errors at some points.
Author Response
Please, find enclosed a detailed response.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsAll my concerns are addressed.