One way to improve traffic is to integrate technologies within autonomous cars, particularly as they are forecast to be soon on our streets, including sensors for driving, and information from different external sources.
Researchers from Facebook and MIT Labs have proposed a new methodology that uses machine learning and satellite imagery to generate street addresses in areas of the world where individual buildings don’t have a unique address.
The Deep Learning-based Hurricane Intensity Estimator is an experimental portal that uses machine learning techniques to analyze spatial patterns in infrared satellite imagery in order to predict tropical cyclone intensity.
New techniques in GIS, remote sensing, and machine learning are incorporating land-based data along with temperature, precipitation and other weather factors in developing more accurate fire prediction models.
Development Seed, working for the World Bank Group, created a methodology for integrating machine learning with manual mapping in order to speed up the mapping of high-voltage (HV) grids in developing countries.