This post originally appeared in OpenMRS Talk as my final presentation.

Operation Theater Module Workflow Enhancements

Mentors: Akshika Wijesundara & Harsha Kumara

Code contribution Summary: GitHub

There’s a certain pleasure in seeing people make use of your work. That’s one of the main driving forces behind the open source philosophy. It’s deeply satisfying to know that your lines of code makes someone’s life easier, even if by just a little bit.
But what about not just making lives easier, but helping to save entire lives? That’s some next level thing. Enter OpenMRS.
This summer I had the opportunity to contribute with code to save lives, and this is my final note about the experience.

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It’s the fourth week, and we’re nearly done with the first round of developments. My main objective for the first round was migrating the Operation Theater module to the latest platform, and I’ve completed about 80% of it. There’s just one more thing to finish – to get the scheduler working.

The OT module uses a tool named Optaplanner for scheduling theater activities. It’s an open source constraint satisfaction solver written in Java. We can model the theater planning activity as a constraint satisfaction problem (CSP) and use Optaplanner to get a somewhat optimal solution in a given amount of time. As you might know, CSPs are  considered to be either NP-complete or harder.

Let’s start with a few definitions before we get to the nitty-gritty.

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So this started as an assignment but turned out to be quite fun by the end of it. We were asked to make a biometric identification system with Java using any biometric identifier. There was one restriction – no libraries were allowed. Out went OpenCV and pretty much anything that could be made to work reliably within the time-frame of a week.

My first thought was to make a voice identifier – a system in which the distinct features of someone’s voice would be saved in order to identify them uniquely. But that turned out to be far more time-consuming than I thought and involved libraries which I could not adopt. There wasn’t much time to write them myself. So after 3 days of struggling, I switched to keystroke dynamics.

What’s keystroke dynamics? It’s the official term for the unique way you type on a keyboard. Turns out that each of us use a keyboard differently – with more than just a change in overall speed. We spend different amounts of time pressing each key and moving onto another, have our own favourites among the Shift keys and show unique patterns while moving from one key to another. And these little things add up to a relatively strong set of features that can uniquely identify someone.

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