In this work I sometimes encounter amusing surprises – such as undocumented product features; or really beautiful and readable code; or telltale comments left by the former programmers like graffiti. (Example: ”This is the fourth time I’m writing this module and I still don’t understand what it’s supposed to do.) Occasionally I find bugs (errors) in the code.
A couple of my cases years ago addressed gaming devices installed in Nevada Casinos. I don’t gamble, but I find the casinos and casino technology fascinating. In these cases I was surprised to quickly receive the source code, without the usual lengthy discovery disputes between the parties.
I learned that the code I received was the version of source code deposited with the Nevada Gaming Control Board. This was news to me. It turns out that no technology may operate in a casino without depositing the designs with the gaming commission so that the computer code could be reviewed for fairness (especially in randomization of outcomes.) This principle – independent review for fairness - always intrigued me. In Nevada’s case it has a name: Regulation 14, which can be found here:
Nevada Gaming Commission Reg 14
The purpose is somewhat like other independent product testing organizations – protecting both the public and the public interest.
Considering the use of red light cams: how does the public know that the systems perform as advertised? That it doesn’t do more? That data isn’t stored in multiple entities. What are the parameters by which a city can customize operation? Are there network backdoors to the data? Are there undocumented features in the software?
However the cameras (and red-light cams) are a way of life at this point.
I recently learned that Automatic License Plate Tracking is now open source software (the OpenALPR effort) . This standard and public domain software suite recognizes the location of the license plate in an image, and then interprets the license plate number. Note that it doesn’t have, or search against, a database of license plate numbers for identifying infomration. There is also a cloud-based service that will interpret a car image that you upload.
“OpenALPR is an open source Automatic License Plate Recognition library written in C++ with bindings in C#, Java, Node.js, and Python. The library analyzes images and video streams to identify license plates. The output is the text representation of any license plate characters.”
See, Open ALPR Open Source License Plate Reader Software
I see a good science project for someone at Menlo-Atherton High to put together a license plate reader and build a database of observed traffic.
