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Article
Peer-Review Record

Ble Based Indoor Positioning System and Minimal Zone Searching Algorithm (MZS) Applied to Visitor Trajectories within a Museum

Appl. Sci. 2021, 11(13), 6107; https://doi.org/10.3390/app11136107
by Richard Jérémy *, Bertet Karell and Faucher Cyril
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Appl. Sci. 2021, 11(13), 6107; https://doi.org/10.3390/app11136107
Submission received: 31 May 2021 / Revised: 22 June 2021 / Accepted: 24 June 2021 / Published: 30 June 2021
(This article belongs to the Special Issue Advanced Sensors and Sensing Technologies for Indoor Localization)

Round 1

Reviewer 1 Report

Some key concerns: (1) The proposed approach should be compared, either qualitatively or experimentally, with other state-of-the-art algorithms. (2) Some important related works are missing: Contour-based Trilateration for Indoor Fingerprinting Localization, ACM SenSys 2015. BlueSentinel: a first approach using iBeacon for an energy efficient occupancy detection system." ACM BuildSys 2014.

Author Response

Dear reviewer,

Thanks you again for your feedbacks. Please see the attachment below to read my response.

Sincerely,

Richard Jérémy

Author Response File: Author Response.pdf

Reviewer 2 Report

The English text must be strongly improved.

The state of the art is clearly described, even thou some more references to alternative approaches to RSSI detection could be useful for the reader, such as:

https://doi.org/10.1109/TSMCC.2007.905750

https://doi.org/10.1109/TCSI.2020.2979347

https://doi.org/10.1109/TIE.2018.2833021

https://doi.org/10.1109/RADIO.2016.7772043

In general, the proposed approach is a good one but the used hardware does not seem suitable to support it. The choice of a 5s windows joint to the complex computations needed define an off-line procedure that could be compatible for a visitor fluxes statistical analysis in a museum, but the  claimed real-time capability is inconsistent with the experiments In which no disturbance (multi-path, obstacles…)  is introduced and assuming ‘perfect’ RSSI measurements.

 

Pg2, r.61 I guess we are talking about a Raspberry Pi or similar system. Please, specify, capitalize the word, and insert any needed reference.

Pg2. R 70 The sentence is rather unclear. What does the method imply? The user positions are monitored for 5 consecutive seconds with an unknown sampling rate, and then averaged?   Otherwise, if the positions are measure once in 5 s, this means that each monitored user can move 3-4 m apart from the starting location in 5s! How many readings are used for the averaging process?

The RSSI gives just an idea of the signal quality as its value depends by many factors (i.e.: multipath, obstacles in the radio link, position of the badge…). Newly, the position is read once in 5 s? How reliable the RSSI reading is?

Pg4 r.93 The equation is valid only in line-of-sight environments, obviously! In a museum or any other type of building the multipath and the obstacles strongly affect the reported estimation.

 

Author Response

Dear reviewer,

Thanks you again for your feedbacks. Please see the attachment below to read my response.

Sincerely,

Richard Jérémy

Author Response File: Author Response.pdf

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