The Technological Development Model for Environmental Monitoring Aimed at the Conservation of the Santa María del Lago Wetland Using IoT Sensors, Satellite Imagery, and Drones

In Bogotá, the absence of integrated data for wetland monitoring persists; therefore, a technological application structured in three phases was developed. In the first phase, information acquisition was conducted through flights using DJI Mini 2 and Phantom 4 Pro drones, with orthomosaics processed in Pix4D and WebODM, together with Landsat and Sentinel satellite imagery obtained from Google Earth Engine. In the second phase, the SIBIA platform was designed. This platform integrates Google Earth Engine panels, machine learning models implemented in Teachable Machine (a low-code environment), and their scaling in Python with OpenCV to classify vegetation and bodies of water. In the third phase, technical and community validation was carried out using IoT sensors, accuracy metrics (RMSE, MAE), and surveys with high reliability (α = 0.894). The results indicate high model accuracy (~0.98–1.00) and the generation of quality orthomosaics. In conclusion, the tool is shown to enhance environmental management and support sustainable decision-making for urban wetlands. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i1.1189Dimensions.Open Alex.