Decoding a Midea Air Conditioner Remote

Last month, I purchased a 6000 BTU Midea window air conditioner (branded Arctic King WWK+06CR5) and thought it would be convenient if I could control it remotely. Doing so would involve decoding the remote’s IR signals; for this, I used a USB Infrared Toy and the PyIrToy Python library. Control signals for other Midea air conditioners have previously been decoded, providing a starting point. Although the signals transmitted by my air conditioner’s R09B/BGCE remote are similar to these previous remotes, they are also sufficiently different such that the actual data transmitted shares little in common. The signal is transmitted on a 38 kHz carrier, with a time base, T, of 21 carrier cycles, approximately 1.1 ms. Each bit consists of the IR transmitter off for 1T followed by it turned on for either 1T for 0 or 3T for 1. Each frame consists of a start pulse, six bytes of data, a middle pulse, and then the inverse of the six data bytes. The start pulse consists of the transmitter off for 8T and then on for 8T; the middle pulse consists of the transmitter off for 1T, on for 9.5T, off for 4T, and then on for 4T.

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Automated Document Creation and Typesetting with LaTeX

Creating a new document class file and then using this class is usually considered the “correct” way to typeset a form or other document generated with data in \LaTeX. However, there’s also the quick-and-dirty method of creating a regular \LaTeX document every time in a script using some sort of string concatenation and then typesetting this, which also has its merits. When a class file is used, the class describes the document look and structure; a new \LaTeX document still needs to be created each time to define the data. Not writing a class file and placing the document look and structure typesetting code directly in the generation script isn’t as clean as the class method as it mixes styling with data, but it does make some things easier. The quick-and-dirty approach doesn’t require knowing the additional \LaTeX language features needed for creating a class, using only what would use in a normal document. In particular, it is useful for automatically generating documents that change in structure based on the input data or other more complicated logic. This can obviously all be implemented as a \LaTeX class since \TeX is a Turing-complete language, but general purpose scripting languages such as Python are easier to use for this, particularly since most programmers use them much more often than they create complicated \LaTeX classes. The quick-and-dirty approach trades the class method’s cleaner design for ease of script creation. However, if the form will ever be created by hand, the class method is definitely superior.

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Amazon Dash Button Teardown

The Amazon Dash Button it an Internet connected button that allows ordering a single product from Amazon. Although it is not something I would ever use, I thought its guts might be interesting and bought two for a grand total of $2.10 with tax and free shipping. Others have already posted about disassembling it, so I’ll focus mostly on the electronics, since the aforementioned blog posts are missing high-resolution images of the circuit board and don’t quite get some details correct.

The first victim is the Cottonelle Dash Button. The outside of the Dash Button consists of a button, a microphone hole, a loop for tying to, and adhesive on the back. The different brands of Dash Buttons have the same model number, JK76PL, differing only in the label.

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OpenStreetMap Baltimore City Buildings and Addresses Import

Two years ago, I started trying to import building footprints and addresses provided by the City of Baltimore into OpenStreetMap but was held up by red tape and eventually gave up.1 The City provides building footprints and parcel data on their open data portal; the download pages for these two datasets list the data as public domain, but the site’s terms of service is the same as the rest of City’s websites, saying the data is copyrighted. I had worked through the technical aspects of preparing and simplifying the building footprints for import and had started working on how to associate addresses from the parcel data but eventually gave up after I was unable to secure the needed licensing clarifications from the Mayor’s Office of Information Technology (MOIT).

This past fall, Elliot Plack, who then worked for Baltimore County GIS and was appointed to the Maryland Open Data Council by Governor O’Malley, got in touch with me about restarting the import, after finishing an import of similar data for the County. After meeting with Jim Garcia from MOIT, he was able to secure the permissions that we needed to proceed with the import. Additionally, he was able to get address point data, which is much superior to and easier to use than the parcel data I was originally going to extract addresses from.
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Bootstrap Navbar without jQuery

While I’m fond of Bootstrap in general, I dislike how much it relies on JavaScript and particularly dislike its dependency on jQuery. I have nothing against using JavaScript for creating interactive content, e.g. web applications, or progressive enhancement, e.g. lightboxes or copying text to the clipboard, but I do take issue with requiring JavaScript for basic site functionality as is the case with Bootstrap’s navbar and dropdowns. What I particularly dislike is that not only does this require JavaScript, but it requires a 32kB JavaScript library, jQuery, to do what would otherwise take less than 1kB of JavaScript. To avoid this when redesigning, I made some modifications to open the navbar’s dropdowns on hover on larger devices and used a small piece of plain JavaScript to operate the menu on small, mobile devices. Unfortunately, this didn’t work properly under iOS, but I recently fixed this. I’m detailing the changes I made in case someone finds them useful.

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