Uploaded on 2017-06-27 by Fernando Ceña Martínez

This is Madison Square Park in New York and I have identified the next two "invisible information": one the density of people in the subway train that stops in this station (23 Street, Lines R-W); and the density of office spaces versus apartments in the buildings of the area. The density of passengers on the train varies along the day being higher at peak hours. Determining this density can help to avoid congestion in the coaches as well as in the network. Trains are forced to miss some stations when platforms and coaches are collapsed with passengers. Controlling this information could help to ease potential congestion. On one hand, the number of trains running at those times could be higher and to facilitate this, reserve trains could be placed on intermediate points of the network, instead of having them on the ending parts of the line. This would mean designing some stations with a bigger capacity, so that they could host these reserve trains. On the other hand, having more extensive real-time information could help commuters to make more informed decisions. In fact, the subway lines could be supported with buses at the peak times, limiting the private traffic, so that the public transportation is given priority.