We develop spatial algorithms to reveal invisible patterns of human behavior and its spatial expression.
Through computer vision and machine learning, NOUMENA implements strategies to track and monitor spatial dynamics, uncovering associations between each individual component. Our aim is to produce informative geographical representations of spatial occupancy to drive strategies such as energy building consumption, urban analytics, farming practices or management for on-site construction.
Semantic segmentation is one of the high-level tasks that paves the way towards complete scene understanding. Image segmentation is a computer vision and machine learning task in which specific regions of an image are labeled according to what’s being shown. Noumena implements metrics and algorithms to reveal associations and map spatial dynamics, to explain patterns of human behaviour and its spatial expression.
Predictive modelling, also called predictive analytics, is a mathematical process that seeks to predict future events or outcomes by analyzing patterns that are likely to forecast future results. These innovative approaches allow identifying future scenarios of spatial transformations and behaviours based on past patterns.
