Using the provided station and my own custom models, I will construct a simple simulation of a train station complete with buildings, roads, and public meeting points. As stated in the brief, the aim of the porosity lens is to "understand people's navigation through an environment". Using the nodes previously researched as a starting point, my porosity lens will seek to address this point by examining firstly how people move through an area, and secondly how many people visit one area or another over a period of time. I will achieve this by using the power of lighting as a visual aid.
My lens will use two different forms of lighting representation. The first will be multiple trails of lights to record human activity in an area, thus demonstrating both how people are moving and where the greatest concentration of activity is. The second will involve gradations of brightness to indicate where the most activity has taken place. To achieve the first effect, multiple AI characters will be deployed throughout the station, and their paths will be recorded using proximity triggers to switch on small lights of varying colours. These lights will remain glowing for a certain amount of time after the characters have passed through them so that a clear path can be discerned.
The second representation will be achieved similarly, but instead of delaying the switching off of the lights, they will remain on once triggered, with new lights being added over the top as more people pass through the area over time. In this way, the areas of the station that received the most human traffic will glow the brightest.