01782nas a2200241   4500000000100000000000100001008004100002260001200043653001800055653003400073653002800107100003000135700002500165700002400190700002400214700003400238245011800272856008000390300001200470490000600482520103800488022001401526       2023                            d  c12/202310aDeep Learning10aGeographic information system10aPool Aerial Recognition1 aHéctor Sánchez San Blas1 aAntía Carmona Balea1 aAndré Sales Mendes1 aLuís Augusto Silva1 aGabriel Villarrubia González00aA Platform for Swimming Pool Detection and Legal Verification Using a Multi-Agent System and Remote Image Sensing  uhttps://www.ijimai.org/journal/sites/default/files/2023-11/ijimai8_4_14.pdf  a153-1650 v83 aSpain 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%.  a1989-1660