Building Rhythms

Reopening the workspace with indoor localisation

Student Report (2021)
Author(s)

M.D. de Jong (TU Delft - Architecture and the Built Environment)

G. Triantafyllou (TU Delft - Architecture and the Built Environment)

G. Spinoza Andreo (TU Delft - Architecture and the Built Environment)

I. Dardavesis (TU Delft - Architecture and the Built Environment)

P. Kumar (TU Delft - Architecture and the Built Environment)

M. Maundri Prihanggo (TU Delft - Architecture and the Built Environment)

Contributor(s)

E. Verbree – Mentor (TU Delft - GIS Technologie)

C.G. van der Vaart – Coach (TU Delft - GIS Technologie)

B. Valks – Coach (TU Delft - Strategic Portfolio Management)

Faculty
Architecture and the Built Environment
Copyright
© 2021 Michiel de Jong, Giorgos Triantafyllou, Guilherme Spinoza Andreo, Ioannis Dardavesis, Pratyush Kumar, Maundri Maundri Prihanggo
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Michiel de Jong, Giorgos Triantafyllou, Guilherme Spinoza Andreo, Ioannis Dardavesis, Pratyush Kumar, Maundri Maundri Prihanggo
Graduation Date
01-07-2021
Awarding Institution
Delft University of Technology
Project
['Synthesis Project 2021']
Programme
['Geomatics']
Related content

Code repository for the project

https://github.com/dumigil/Building-Rhythms
Faculty
Architecture and the Built Environment
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Indoor localisation methods are an essential part for the management of COVID-19 restrictions, social distancing, and the flow of people in the indoor environment. Moving towards an open work space in this scenario requires effective real-time localisation services and tools, along with a comprehensive understanding of the 3D indoor space. This project’s main objective is to analyse how ArcGIS Indoors can be used with location awareness methods to elaborate and develop space management tools for COVID­-19 restrictions in order to reopen the workspace for TU Delft Campus. This was accomplished by using six Arduino micro controllers, which were programmed in C++ to scan all available Wi-­Fi fingerprints in the east wing of the Faculty of Architecture and the Built Environment of TU Delft and send over the data to an ArcGIS Indoor Information Model (AIIM). The data stored on the AIIM is then accessed using the app on the user’s Android device using REST Application Programming Interface (API) where a kNN based matching algorithm then identifies the location of the user. The results show that the localisation is not consistent for rooms that are directly above each other or share common access points. However, when functioning to locate different tables inside a room, the system proved to uniquely distinguish between the specific tables. As a result, we can conclude that based on the size of the rooms, more Arduino devices should be installed to achieve an ideal accuracy. Finally, recommendations are made for the continuation of this research.

Files

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