Hi there. Yes, I know, it’s been 2 years since I last posted something on my website. Mea Culpa, I installed Joomla, I’m not much for website design, been busy, that sort of thing.
So how’s the spouse and kids? Really?! Well congrats, I’m glad to hear that. Except for the part about the restraining order, that’s a shame.
But hey the real reason why I’m here is to talk about an idea that popped into my head while I was zoning out along I-85 when heading back from a conference earlier this week. Being a responsible adult and all I tried to keep it down to only the “prayer for judgment” speeds and not “Judge Dredd” speeds. This is easy enough with cruise-control until you suddenly realize there’s a car ahead of you or behind you and you’re not sure if it’s a cop or not. And you don’t have radar detectors because you’re a law abiding citizen, damn it!
It occurred to me that we have all the technology to build an open source surveillance system for tracking and identifying police cars on the road. Now doing something like this of course requires making sure everything is done legally, and that has to account for differing laws between states and counties. But let’s push that down further into the article and jump into a technical outline of how to do this.
(And yes, this is a way to turn universal surveillance by law enforcement back on them).
To start with the idea of a Collaborative Cop Identifier System (CCIS) requires servers and software to be able to pull in data from many contributors, process it and produce useful output. The CCIS would likely use a typical virtual hosting platform with servers for databases, webservers to handle automated and human requests, and app servers to run data processing tasks that are computationally intensive. Let’s assume relatively unlimited financial resources for this project, so everything can be hosted in a nice redundant datacenter (*cough*), we have paid coders to do dev work and sysadmins to keep everything running and monitor for outages.
CCIS would primarily be used by people driving cars, so it’d have to be optimized for use over WiFi/Cell networks. We’d need support for speech input and output, and a robust API so a lot of client platforms can be supported (cellphones, tablets, etc).
The core model would be individual users equipping their cars with a set of sensors, running a CCIS client application on an appropriate mobile device, pairing all this to an account on the CCIS backend systems and then just driving like they would normally. Data would be gathered by the client system and sent to CCIS servers for processing, and real-time feedback would be fed back in the form of voice commands, audio signals and/or visual cues.