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Article
Peer-Review Record

Integrated Technologies for Smart Building Energy Systems Refurbishment: A Case Study in Italy

Buildings 2025, 15(7), 1041; https://doi.org/10.3390/buildings15071041
by Lorenzo Villani 1,*, Martina Casciola 2 and Davide Astiaso Garcia 1
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3:
Buildings 2025, 15(7), 1041; https://doi.org/10.3390/buildings15071041
Submission received: 18 February 2025 / Revised: 14 March 2025 / Accepted: 21 March 2025 / Published: 24 March 2025
(This article belongs to the Special Issue Sustainable and Smart Energy Systems in the Built Environment)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper focuses on the field of smart building energy system renovation, innovatively applying cutting-edge technologies such as machine learning, the Internet of Things, and Building Information Modeling (BIM) to a practical case of hotel renovation in Italy. It proposes an innovative renovation plan aimed at improving the energy efficiency of the hotel, optimizing indoor comfort, and providing new ideas and practical examples for the sustainable development of the hotel industry. This plan demonstrates a certain level of innovation and practical value. However, there are still some details that could be further optimized to enhance the readability and scientific rigor of the article. Here are my suggestions:

 

  1. In line 206, is formula (1) original? If not, please add a citation.
  2. The paper uses meteorological data from 1980 to 2016 for climate analysis, but recent years have seen significant climate changes. It might be worth supplementing more recent data or conducting sensitivity analysis to explore the impact of climate data changes on the research results.
  3. It is recommended to merge Sections 2 and 3 and conduct an analysis of the case study based on the proposed methodology.
  4. In the BIM and ML model construction section, the assumptions and simplifications of the model are not clearly explained. These should be elaborated on so that readers understand the scope of applicability of the model. Additionally, include the model validation process by comparing with actual monitoring data to assess the reliability and accuracy of the model.
  5. Although various technology integrations are proposed, the details of the fusion between technologies and the analysis of implementation challenges are insufficient. This can be appropriately supplemented.
  6. Most of the results in the paper are presented in tabular form, which may be overwhelming. It is recommended to use more charts and graphs to make the data more intuitive and easier for readers to understand key information.
  7. The “Discussion” section needs to include references to relevant literature to substantiate the feasibility of the experimental results and to provide a comparative discussion, such as comparing with other similar hotel renovation cases to highlight the advantages and uniqueness of the proposed methodology.
  8. The “Discussion” section should also include discussions on limitations and future development trends.
  9. The paper has relatively few references; it would be beneficial to supplement the relevant literature in the field to enhance the scientific nature of the paper .

 

Author Response

Thanks for your revision. Please see the attachment in .docx extension.  

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

How were the photovoltaic panels and solar collectors seamlessly integrated with the building's electrical grid? Were smart inverters and energy storage systems part of the setup, and if so, what control mechanisms were put in place to manage their operation?

What was the actual energy conversion efficiency of the solar systems in this study? Which factors played a major role in influencing efficiency, and what strategies were implemented to minimize their negative effects?

Did the research involve an Energy Management System (EMS) to balance energy consumption and production within the building? How were the EMS control algorithms crafted, and what performance metrics were applied to gauge their effectiveness?

In what ways did the hybrid HVAC system communicate with the building's electrical grid? Were load management techniques employed to mitigate peak consumption, and how did these strategies impact grid stability?

What insights did the techno-economic analysis reveal about integrating renewable energy sources into this project? What were the calculated Return on Investment (ROI) and Payback Period, and how were these financial indicators derived?

How was the custom machine learning algorithm for the HVAC system designed and implemented? What data sources were used for training, and how was its performance validated in practical, real-world scenarios?

What optimization techniques were leveraged for feature selection within the machine learning algorithm? What selection criteria were prioritized, and how did these choices affect the algorithm's accuracy and computational efficiency?

How were temporal models applied to forecast the long-term performance of the building's energy systems? What was the prediction accuracy, and how consistently reliable were these models over time?

How was the building's energy performance evaluated under real operating conditions? What specific metrics were employed to assess energy efficiency, system reliability, and occupant comfort?

How was the environmental and sustainability impact of the integrated technologies measured? What key performance indicators (KPIs) were used to quantify environmental benefits and ensure long-term sustainable outcomes?

Author Response

Thank you for your revision. Please see the attachment in .docx extension.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This manuscript presented the study on the use of building energy systems using Machine 11 
Learning (ML), the Internet of Things (IoT), and Building Information Modelling (BIM) in a hotel 12 retrofit in Italy. The research content is substantial, and the conclusions are reasonably sound. However, there are also some issues that need to be addressed:
- Authors must mention the methodology data in abstract section for clear understanding about the methodology used for the research. 
- In introduction section authors must add citation to Bardukova L. 2023. This citation mistake was observed throughout the manuscript. Correct this!!
- Authors must add citation for the codal specification for all test procedures.  
- Figure 3 and 4 were not cited in text....Correct this and also incorporate throughout the whole manuscript. 
- Table was also not cited....Correct this. 
-  Table preparation is not as per the journal....It is suggested to prepare accordingly.
- Mention some supporting literature to validate your result and discussion for proper understanding.
- Present conclusion in bullet points. 

Author Response

Thanks for your revision. Please see the attachment in .docx extension. 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have adequately addressed my previous review comments, and I recommend considering the paper for publication.

Reviewer 2 Report

Comments and Suggestions for Authors

I hava no other comment.

Reviewer 3 Report

Comments and Suggestions for Authors

Authors have successfully addressed all the comments. So final decision from my side is the ACCEPTANCE 

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