A Platform for Swimming Pool Detection and Legal Verification Using a Multi-Agent System and Remote Image Sensing.

Héctor Sánchez San Blas; Antía Carmona Balea; André Sales Mendes; Luís Augusto Silva; Gabriel Villarrubia González

doi:10.9781/ijimai.2023.01.002

Authors

Héctor Sánchez San Blas Universidad de Salamanca
Antía Carmona Balea Universidad de Salamanca
André Sales Mendes Universidad de Salamanca
Luís Augusto Silva Universidad de Salamanca
Gabriel Villarrubia González Universidad de Salamanca

DOI:

https://doi.org/10.9781/ijimai.2023.01.002

Keywords:

Deep Learning, Geographic information system, Pool Aerial Recognition

Supporting Agencies

Héctor Sánchez San Blas's research is supported by the Spanish Ministry of Universities (FPU Fellowship under Grant FPU20/03014). The research of Luis Augusto Silva has been funded by the call for predoctoral contracts USAL 2021, co-financed by Banco Santander.

Abstract

Spain is the second country in Europe with the most swimming pools. However, the legal literature estimates that 20% of swimming pools are not declared or irregular.The administration has a corps of people who manually analyze satellite or drone images to detect illegal or irregular structures. This method is costly in terms of effort and time, and it is also a method based on the subjectivity of the person carrying it out. This proposal aims to design a platform that allows the automatic detection of irregular pools. Using geographic information tools (GIS) based on orthophotography, combined with advanced machine learning techniques for object detection, allows this work. Furthermore, using a multi-agent architecture allows the system to be modular, with the possibility of the different parts of the system working together, balancing the workload. The proposed system has been validated by testing it in different towns in Spain. The system has shown promisin results in performing this task, with an F1-Score of 97.1%.

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