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This study focuses on updating existing maps and enhancing their application for more efficient infrastructure management at UJLoG. The process was carried out in two distinct phases. First, it involved updating the educational building map based on a 2020 map, created through object-oriented supervised classification of a Very High Resolution (VHR) satellite image from the GeoEYE-1 satellite. The second phase involved the proposal and design of an object-oriented model using the Unified Modeling Language (UML) to optimize map utilization. The results indicate the presence of fifty-six (56) classrooms dedicated to educational activities, including sixteen (16) newly acquired spaces. Additionally, the study’s outcomes support three key decision-making processes: the development of an interactive online map of teaching locations accessible at any time, the ability to generate detailed statistics on the utilization of these teaching areas, and enhanced oversight and monitoring of the usage, occupancy, and dynamics of the educational buildings used for training and other academic activities. The overall contribution of this study aims to optimize the management of education at UJLoG by developing a spatial model for planning educational infrastructures. The use of the k-NN algorithm enables the updating of building maps, thereby improving the accuracy and relevance of the available data.

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Building Mapping for Implementing an Object-Oriented Model of Educational Infrastructure Usage at Jean Lorougnon Guédé (UJLoG) University in Central-Western Côte d’Ivoire

  • 会议论文

  • 发表日期：

    2025年

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  • N’guessan Patrice Akoguhi,
  • Kpangni Alex Jérémie Koua,
  • Egomli Stanislas Assohoun,
  • N’dri Pascal Kouame,
  • Koffi Fernand Kouame

摘要

This study focuses on updating existing maps and enhancing their application for more efficient infrastructure management at UJLoG. The process was carried out in two distinct phases. First, it involved updating the educational building map based on a 2020 map, created through object-oriented supervised classification of a Very High Resolution (VHR) satellite image from the GeoEYE-1 satellite. The second phase involved the proposal and design of an object-oriented model using the Unified Modeling Language (UML) to optimize map utilization. The results indicate the presence of fifty-six (56) classrooms dedicated to educational activities, including sixteen (16) newly acquired spaces. Additionally, the study’s outcomes support three key decision-making processes: the development of an interactive online map of teaching locations accessible at any time, the ability to generate detailed statistics on the utilization of these teaching areas, and enhanced oversight and monitoring of the usage, occupancy, and dynamics of the educational buildings used for training and other academic activities. The overall contribution of this study aims to optimize the management of education at UJLoG by developing a spatial model for planning educational infrastructures. The use of the k-NN algorithm enables the updating of building maps, thereby improving the accuracy and relevance of the available data.