We’ve been seeing a lot of garage door opener hacks, whether it’s because one person inspired everyone else to build their own Internet-connected GDO or because there’s something in the water that’s caused the simultaneous building of one specific type of project, we’re not sure. However, the latest one we’ve seen adds a little something extra: motion-based security.
[DeckerEgo] really went all out with this one, too. The core of the project is a Raspberry Pi hardwired to a universal garage door remote. The Pi also handles a small webcam and runs a program called motion, which is a Linux program that allows for all kinds of webcam fun including motion detection. While the other builds we see usually use a button or limit switch to tell whether the door is open or closed, this one just watches the door with the webcam so [DeckerEgo] can actually see what’s going on in the garage. As a bonus, the motion software can be configured to alert him if anything suspicious is going on in the garage.
The build is full-featured as well, with an interesting user interface overlaid on the live picture of the garage door. According to [DeckerEgo] the camera is a necessity because he wouldn’t trust a simple status indicator, but if you wanted to try one of those before breaking out the Raspberry Pi, we’ve featured one recently that you can check out.
Fans of the bouncing lamp from the Pixar corporate logo will enjoy [Daniel]’s latest project. It’s a motion controlled desk lamp that uses ultrasonic sensors to control its physical position.
The core of the project is an Arduino and the three ultrasonic sensors. The sensors act as range finders, and when they are all working together under the direction of the microcontroller they can tell which direction a hand was moving when it passed by. This information is used to drive two servos, one in the base and one on the lamp’s arm.
The project requires an articulating desk lamp of some sort (others besides the specific one [Daniel] used shouldn’t be much of a problem as long as they bend in the same way). Most hackers will have the rest of the parts on hand, with the possible exception of the rangefinder. The code is up on the project site for a look-see or in case you want to build your own.
The only problem that [Daniel] had when putting this all together was that the base was a little wobbly. He was able to fix that with some thumbtacks, and we think the next step for the project should be switching the light on and off over the internet.
[Gil] sent in an awesome paper from this year’s SIGGRAPH. It’s a way to detect subtle changes in a video feed from [Hao-Yu Wu, et al.] at the MIT CS and AI lab and Quanta Research. To get a feel for what this paper is about, check out the video and come back when you pick your jaw off the floor.
The project works by detecting and amplifying very small changes in color occurring in several frames of video. From the demo, the researchers were able to detect someone’s pulse by noting the very minute changes in the color of their skin whenever their face is pumped full of blood.
A neat side effect of detecting small changes in color is the ability to also detect motion. In the video, there’s an example of detecting someone’s pulse by exaggerating the expanding artery in someone’s wrist, and the change in a shadow produced by the sun over the course of 15 seconds. This is Batman-level tech here, and we can’t wait to see an OpenCV library for this.
Even though the researchers have shown an extremely limited use case – just pulses and breathing – we’re seeing a whole lot of potential applications. We’d love to see an open source version of this tech turned into a lie detector for the upcoming US presidential debates, and the motion exaggeration is perfect for showing why every sports referee is blind as a bat.
If you want to read the actual paper, here’s the PDF. As always, video after the break.
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