Posted onFebruary 21, 2014
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This is the bus usage from october 2008,2010,2012 and the last is whether these bus routes increased or decreased. The rail stations with the same information is a view with a geom but when you go to import it into qgis it reads that it has a geom and it reads it as a file that can import but it says that its not an acceptable file
The intent of this post is to give potential ways of tracking people on CTA buses. There is currently no way of tracking individuals, nor who gets off at what stations. With the hopes of providing a prototype for a system that will give the CTA a more comprehensive analysis of their riders, several factors will be necessary.
1. There needs to be an accurate way to detect when a person boards the bus as well as when they get off.
2. There needs to be a way to detect multiple people and keep track of them as they shift through the bus.
The wide spread use of cell phones would offer one way of tracking peoples movements. Cell phone detectors are common in prisons as cell phones have become one of the largest contraband items in prisons. These systems are relatively inexpensive and they are non intrusive, meaning they detect the radiation given off by phones and do not actually monitor phone usage. This second part is important because it allows us to track people without illegally monitoring their calls, texts, or data streaming. Here are links to the two most commonly used companies for cell phone detection.
This is geared more towards protecting a wifi network but it still is capable of detecting cell phone uses anywhere from 5-100 ft. If hacked and set with an aduino circuit board this would give the opportunity to monitor the radiation given off by cell phones with reference to location on the bus.
The second link is to the far more common BVS systems cell phone detector
This system is as small as a deck of cards, which would be advantageous on a crowded bus. This detection is up to 75 ft which allows it to detect anywhere on a bus. If properly used this could allow for detection of peoples cell phones when they get on the bus and when they get off, essentially allowing to track multiple people and to better determine what are the busiest bus stops.
The suggested prototype for this will not give the information on what the best bus routes but it will give the potential prototype for collecting the information necessary to determine this in the future.
The last link is for a tiny homemade motion detector. This is an alternative to cell phone detection but it would be difficult to get a comprehensive understanding of the amount of people on the bus as it monitors motion and cannot determine individuals