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Peer-Review Record

A Smart Campus’ Digital Twin for Sustainable Comfort Monitoring

Sustainability 2020, 12(21), 9196; https://doi.org/10.3390/su12219196
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Basheer Qolomany
Sustainability 2020, 12(21), 9196; https://doi.org/10.3390/su12219196
Received: 21 September 2020 / Revised: 23 October 2020 / Accepted: 3 November 2020 / Published: 5 November 2020

Round 1

Reviewer 1 Report

This study explore the structures, processes, and activities related to SC concept that promote sustainability from a multicultural and interdisciplinary perspective. Today, there are nineteen Lasallian universities involved in a global initiative to promote sustainability through research projects focused on campus transitions via sustainability development projects.

As a whole, the content of the manuscript is of novelty and logicality.

Author Response

Thank you very much for your comments and appreciations.

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper investigates the integration of BIM with IoT-based WSN in the campus building. Various IoTs were installed and measured but not that meaningful/scientific results were discussed.

Was the Revit simulation calibrated with actual measurements such as indoor air temperature and energy consumption of the HVAC? Without this, digital twin building does not reflect the thermal behavior of the target building.

The role of digital twin building and measured data should be clearly stated, and corresponding results need to be discussed as results.

Author Response

Thank you very much for the comments and appreciations made on the paper. We have been working to improve some explanations about how we have updated real-time information in the digital twin building to reflect current environmental parameters. We highlighted the changes—coming from the previous review—to our manuscript within the document by using the highlighter. Regarding your appreciations, we absolutely agree with you. Although the BIM model explanation and python code is out of the scope of this paper, we have added the following explanation:

If you look at Figure 11 more closely, you will notice that the update of the real-time sensed data is performed from the IoT deployed physical infrastructure to the Revit model through the Dynamo interface. Thus, the digital twin of the Smart Campus is updated by accessing real-time stored data in the cloud (see Figure 16: Dynamo flow representing 1) the current environmental data collection and rendering from each node stored in the database and 2) the current emotion data collection and rendering from each camera stored in the database.).

Furthermore, we try to clarify the role of the digital twin model and how to use real-time sensed data in our model by adding the following paragraph and new figure:

With the geometric room parameters defined in our BIM model, sensed information is collected from the database. It is then submitted by a python-script object (Figure 18: Dynamo flow representing IEQ calculation), which calculates the IEQ index based on the ASHRAE standard, and figures out the proposed weighted model stated in this paper for the real-time IEQ value.

Author Response File: Author Response.pdf

Reviewer 3 Report

The authors propose a smart campus concept that investigates the integration of Building Information Modeling (BIM) with IoT-based Wireless Sensors Networks (WSN) to improve sustainability beyond that of a traditional campus with heterogeneous learning activities.  I have the following issues need to be solved:

  1. It would be better to use bullets to summarize the contributions.
  2. I suggest adding a table of abbreviations.
  3. In Sec. 1.4, I suggest adding a figure that shows the hierarchical structure (Layered architecture) of the proposed framework and relationship among different modules.
  4. In table 1, I suggest adding some platforms that belong to type (4) End to End connectivity of the IoT platform.
  5. I suggest adding a section related to the real-life sustainability challenges and future research directions in the smart campus environment.
  6. The paper needs a detailed grammar/typo check.

Author Response

Thank you very much for your valuable contributions. We highlighted the changes—coming from the previous review—to our manuscript within the document by using the highlighter.

  1. We have added some observations along the paper about our vision of the smart campus concept that should improve the explanation and understanding. In this current revision, we have enhanced the paper's quality by providing more in-depth information bullets with the contributions. In conclusion, we can summarize the objectives and contributions of our work in the following:
  • This paper proposes a digital twin modeling that merges well-known approaches used in SC to integrate a set of advanced intelligent features: The use of technology for a digital SC by using an IoT network and cloud computing that transform university spaces into information sources for intelligent decision-making. SC will adopt the technology paradigm in order to support multiple tasks in multi-functional buildings (teaching, research, management, and services) and include different users (students, researchers, guests, etc.). Our proposal is to develop the SC through the efficient use of resources, thereby reducing operational costs and making life more comfortable.
  • Our contributions tackle with three intelligence domains that should be equipped with various capabilities [8][52]: 1) Green Campus, in line with the issue of climate change that includes the intelligent energy consumption and the implementation of sensor technology for accurate reporting, 2) Healthy Campus, to monitor and promote the level of comfort by tracking and recording the status of the campus activity and, 3) real-time Facility Management, which includes facilities, infrastructures and the people (staff, students and visitors).
  • The proposed SC concept is not limited to support smart learning processes but also supports other aspects of campus life (the comfort of the academy community understood as a quality metric).
  • In the developed model, all the smart campus devices, including energy consumption performance and the comfort evaluation dashboard, can be accessed by information stakeholders through the BIM platform. This middleware facilitates the interoperability and co-working between engineering and architecture staff by promoting an interdisciplinary task force. We envisage the fact that if sustainable policies have to be defined, an interdisciplinary team could easily cope with the identification of patterns and the suitability assessment of the proposed improvements.
  • The main goal of our ongoing research project is to develop SC concepts, digital twin and complex adaptive systems, and identify the main distinctive characteristics, modules, and technologies of a multi-disciplinary SC. The aim is to improve sustainability beyond that of a traditional campus with heterogeneous learning activities.

 

  1. Thank you for your suggestion. We have added Appendix A: Acronyms
  2. Thank you for your suggestion. We have added Figure 1: Complex Adaptive System and SIoT relationships in the Smart Campus digital twin.
  3. Thank you for your suggestion. You are right! In its origin, the Google IoT platform and Kaa IoT platform were designed as a type 3 (Developer Friendly IoT Cloud platform). However, currently, after the improvements carried out in the last year, they are good examples of type 4 (End to End connectivity IoT cloud Platform) as you can see in:

- Google IoT cloud [https://cloud.google.com/iot/docs/samples/end-to-end-sample]

- Kaa IoT [https://www.kaaproject.org/overview])

  1. Thank you for your suggestion. We have enhanced section 2 with related work in order to set the focus in the contributions of our work:

The term Smart Campus (SC) has been used to refer to digital online platforms that manage university content and those set of techniques aimed to increase university student smartness and knowledge transmission ease [51]. Several research questions have to be addressed in order to model the SC concept. In [52], a systematic literature review is performed to explain the problem by analyzing more than 300 tracked publications: 1) What are the SC features? 2) What kinds of technologies support the implementation? 3) Is there any standard model? 4) What are the main applications? And 5) What are the SC contributions? The main conclusion of the research community is that the research in the smart campus area is still growing, and there is no standard used for the development of smart campus concept and implementation. In essence, an SC is generally considered as the integration of cloud computing and the IoT that pursue intelligent management, teaching, research, and other activities of universities [8][52][53]. As stated in [8][52], the main challenges of a sustainable SC are 1) the promotion of intelligent energy management by inner facility management, 2) the existence of a digital twin model that facilitates simulations and knowledge extraction for intelligent decision-making and, 3) obtaining real-time data to render campus map information ergonomically, to generate event response and warning services, etc.

  1. The paper has been proofread and corrected by Professor Lisa Kinnear, a native English reviewer of our University. All the grammatical errors and typos have been corrected.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

I wish the paper is more scientific. I appreciate the authors for the revision and comment responses. Thanks.

Reviewer 3 Report

The authors have addressed all of my comments. I recommend acceptance.

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