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Hyperautomation using artificial intelligence and geospatial technology. Our startup specializes in providing efficient and accurate solutions for monitoring and analyzing changes in specific regions, using satellite and drone imagery.
Our platform is based on neural networks, which are machine learning algorithms capable of identifying patterns and performing complex tasks. We use these networks to process and analyze satellite imagery, extracting valuable information about changes in the terrain, such as deforestation, irregular construction, and other relevant events.
Applications
Monitoring of deforestation and invasions of environmental preservation areas
Detection of new irregular constructions
Mapping of changes in land use
Analysis of environmental risks
Urban and territorial planning
Our platform can be customized for a myriad of highly complex applications.
We master a set of essential technologies for the development of robust and innovative solutions in artificial intelligence and geospatial technology. Our main programming languages include Python, with its powerful libraries such as TensorFlow and PyTorch for building and training neural network models, as well as GDAL and Rasterio for geospatial image processing. We utilize frameworks like Keras and Fast.ai to streamline the development of deep learning models, and explore neural network architectures such as CNNs (Convolutional Neural Networks) for image analysis, RNNs (Recurrent Neural Networks) for processing temporal sequences, and Transformers to handle complex geospatial data. Expertise in OpenCV ensures efficient image processing, while Google Earth Engine allows access and analysis of large geospatial datasets, including high-resolution satellite imagery. Our knowledge also encompasses pre-trained models such as ResNet, Inception and U-Net, which are optimized for specific computer vision tasks and satellite imagery analysis. This combination of technologies allows us to extract accurate and relevant information from satellite imagery, driving the automation of services and strategic decision-making in various areas.
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