Uploaded on 2015-04-28 by jqalves

[1]: https://edxuploads.s3.amazonaws.com/14302366137127509.jpg In this photo we can see a transportation and shopping interface in Vila Nova de Gaia, Portugal. There is a light train stop, a bus stop on the other side of the street and shopping center behind. Since this is also a residential area it is one of the major hubs in the city, since people can travel by light train or bus to the neighboring city of Porto (just on the other bank of the river Douro) or to more remote residential areas. Citizens can do their shopping when they return home from work, can easily commute with other types of transportation (bus just opposite, suburban trains at close distance) and since this is also a residential area it is always relatively busy, but not unpleasantly crowded, both during working days and weekends. The area went through major transformation in the last 15/20 years changing from a major road full with private cars and highly polluting old buses, to an area where private cars are not too many and most travelling is done by public transportation. Most of the invisible information that can be extracted from this location is related to how people travel, which are the busiest routes, the ones less used and also information related to shopping habits can be extracted - who are the shoppers, where do they come from and even what kind of goods they buy (if we relate travel profiles - through traveling cards - and shopping profiles - through shopping cards). Other invisible information that can be extracted might be related to public lighting maintenance, for example monitoring how many hours each individual light bulb has been used or water distribution systems underground - by monitoring pressure levels in the water distribution system we can tell when there is a leakage . Since the use of transportation information was already discussed in the course material I think it may be more interesting to focus on the lighting and water related invisible information. By managing invisible information from lighting systems we can replace a light bulb before it burns out, preventing shades at night that may affect safety and so improving citizen experience in the city. Also this can be used to monitor the life span of light bulbs, benchmarking suppliers specifications and potentially holding suppliers responsible in case reality doesn't meet specifications (City will be using citizens money wisely...) Regarding water leakages, if they are detected in an early stage, property damage and inconvenience to citizens can be avoided, not to say that in some cases this can even cause serious accidents, if not repaired on time. Also reducing water leakage (sometimes as big as 30% of total water pumped into the network) can be a good way of improving water conservation, a major concern to some cities around the world.