Helping to detect legal swimming pools with deep learning and data visualization

Bruno Lima, Luís Ferreira, João Martinho Moura

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)
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Abstract

The municipalities have, as a primary responsibility, the administrative management of their territory. The use of geographic information systems (GIS) and orthophoto maps can help to handle this task. One of the great difficulties they face is related to the continuous and quick changes that the territory suffers, and whose inspection is challenging to support. An example of this is the maintenance of the swimming pool registration system, in order to validate or license them. Indeed, it requires a substantial manual intervention, yet. This paper describes a system prototype for helping on detecting swimming pools on aerial images. It explores and integrates artificial intelligence (AI), systems integration, GIS, and data visualization. The AI improves the detection of objects, and middleware supports the integration of the detection results with other municipality systems for georeferencing and private property data licensing data crossing. To the innovative interoperability services, visualization libraries were explored, and an advanced visualization and analysis system was constructed. A dataset of aerial images of swimming pools and correspondent classification metadata was created. The model was trained with several convolutional neural networks in order to obtain and compare the precision results. The more accurate model is described.
Original languageEnglish
Pages (from-to)1058-1065
Number of pages8
JournalProcedia Computer Science
Volume181
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event2020 International Conference on ENTERprise Information Systems - International Conference on Project MANagement and International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 2020 - Vilamoura, Portugal
Duration: 21 Oct 202023 Oct 2020

Keywords

  • Artificial intelligence
  • Data visualization
  • Detection
  • GIS
  • Orthophotomaps
  • Pattern recognition

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