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Article
Peer-Review Record

EmotIoT: An IoT System to Improve Users’ Wellbeing

Appl. Sci. 2022, 12(12), 5804; https://doi.org/10.3390/app12125804
by Javier Navarro-Alamán 1,*, Raquel Lacuesta 1,2, Iván García-Magariño 3,4 and Jaime Lloret 5,6
Appl. Sci. 2022, 12(12), 5804; https://doi.org/10.3390/app12125804
Submission received: 12 May 2022 / Revised: 2 June 2022 / Accepted: 6 June 2022 / Published: 7 June 2022
(This article belongs to the Special Issue Internet of Things (IoT) in Smart Cities)

Round 1

Reviewer 1 Report

It is recommended to expand the bibliography, this topic is interesting and there are significant advances on it, which were developed because of COVID19.

In the body of the document, it is required to adjust the referencing in order to avoid confusion with plagiarism and reduce the degree of similarity.

It is necessary to expand the explanation of the architecture and the algorithm, as well as the classification selection method according to the results obtained.

It is necessary to review and expand the conclusions.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper considered that IoT can be applied in the emotional domain, and aims to design IoT systems from the perspective of emotional and intelligent adaptation rules. The system is developed in six stages, and the final effect is to analyze the current user state and predict future user emotions to recommend follow-up activities. I have the following comments.

(1) What is the most challenging aspect of your proposal compared to those in the existing literature?

(2) In the fourth stage of the system, please further explain why the data is divided into three parts according to the acquisition time.

(3) In Section 4.2, three grid diagrams of the beginning, the process, and the end are given. The authors should explain the reason that only the details of the transition between the beginning and the end are mentioned at the end.

(4) This system collects a large amount of data through the Internet of things, so the subsequent data set may become larger and larger. The authors should explain the advantages of your proposed decision tree algorithm for processing large datasets.

(5) It is suggested to add more recent references in the introduction, e.g., SWIPT Cooperative Spectrum Sharing for 6G-Enabled Cognitive IoT Network.

(6) There are a number of typographical and grammatical errors in the paper. For example, section 4.3 is written as 4.1, and HRV and EAD in the text description of section 4.1 are written as VFC and AED.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Suggestions were heeded.

Reviewer 2 Report

No more comments.

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