Wolfram Language can combine graph theory and image processing functionality to analyze images from traffic cameras and plan commute routes during rush hour. This webinar presents a multiparadigm data science workflow that starts with images from London's "JamCam" traffic cameras and ends with recommendations to commuters about the least-busy path from home to work. The publicly available API is used to find images from London traffic cameras, and machine learning is used to detect cars in the cleaned-up images. With the help of some classical image processing on geographic maps, Wolfram Language is used to create a graph of London's road network, matching camera locations to corresponding nodes on the network. All that remains is the application of graph theory to find the appropriate path through the network that avoids the jammed-up nodes.