[G. Eric Rogers] is a radar-systems engineer who just happens to live within sight of the aircraft approach path for the local airport. We wonder if that was one of the criteria when looking for a home? Naturally, he wanted his own home-based system for tracking the airplanes. He ended up repurposing a motorized telescope for this purpose.
The system does not actually use Radar for tracking. Instead, the camera strapped to the telescope is feeding a video experimenter shield. A tracking algorithm analyzes the video and extrapolates vector data. From there, the base unit can be controlled by the Arduino via an RS232 interface.
There are some bugs in the system right now. The Arduino has something of an ADHD problem, losing interesting and going to sleep in the middle of the tracking process. [Eric’s] workaround uses the RS232 board to periodically reset the Arduino, but he hopes to squash this bug soon.
Check out this solar-powered Stirling engine (translated). The build is part of a high school class and they packed in some really nice features. The first is the parabolic mirror which focuses the sun’s rays on the chamber of the engine. The heat is what makes it go, and the video after the breaks shows it doing just that.
But the concept behind the mirror makes for an interesting challenge. The light energy is focused at a narrow point. When the sun moves in the sky that point will no longer be at an efficient position to power the engine. This issue is solved by a pair of stepper motors which can reposition the dish. It’s done automatically by an Arduino Uno which makes readings from four LDR (photoresistors) in that cardboard tube mounted at the top of the dish. If the light intensity is the same for all four, then the tube is pointed at the sun. If not, the motors are tweaked to get the best angle possible.
Continue reading “Sun-powered Stirling engine with automatic tracking”
Many of the hacks featured here inspire others to build on the creator’s work, and on occasion the positive feedback brings the hack to market. Last year we told you about [Wayne’s] creation, a system aimed at tracking down would-be game console thieves. He received a bunch of requests to document the tracker in full, so he decided to revise his creation and release it as Open Source Hardware.
As you might remember, his original tracking device was powered by an Arduino, which monitored an accelerometer and GPS sensor, reporting coordinates and movements to his mobile phone on demand. He combined the disparate components together on a single board, and started a Kickstarter for the project.
Aside from his original purpose of tracking stolen goods, he lists off an array of other uses, such as tracking the driving habits of your newly licensed teen, geofencing objects in certain areas and more.
If an SMS controlled all-in-one tracking system is something you might be interested in, check out his Kickstarter, or take a look at the documentation and build one of your own.
One of [Wayne’s] relatives had their house robbed during a blizzard/extended power outage, and as is typically the case, none of the stolen items were recovered. His nephew’s PS3 was among the pilfered belongings, which didn’t sit well with him. Taking a cue from police “bait cars”, he thought it would be cool to fit a dummy game console with a tracking device, should anything similar happen in the future.
He bought a hollowed out PS3 shell on eBay, filling it with an Arduino, an accelerometer, a GPS sensor, a small GSM modem with a prepaid SIM card, and a reasonably sized LiPoly battery. The system usually sits in a sleeping state, but when the accelerometer senses motion, the Arduino powers up the GSM modem and sends an SMS security alert to his mobile phone. Using his phone to control the tracking system via SMS, he can request GPS coordinates and directional information, which can then be relayed to the police.
His tracking system is a great idea since hawking stolen game consoles are easy money for thieves. If there happens to be a string of robberies in your neighborhood, you could certainly rest a little bit easier knowing that your Playstation doppelganger will let you know if someone is looting your house.
It looks like the world of Kinect hacks is about to get a bit more interesting.
While many of the Kinect-based projects we see use one or two units, this 3D telepresence system developed by UNC Chapel Hill student [Andrew Maimone] under the guidance of [Henry Fuchs] has them all beat.
The setup uses up to four Kinect sensors in a single endpoint, capturing images from various angles before they are processed using GPU-accelerated filters. The video captured by the cameras is processed in a series of steps, filling holes and adjusting colors to create a mesh image. Once the video streams have been processed, they are overlaid with one another to form a complete 3D image.
The result is an awesome real-time 3D rendering of the subject and surrounding room that reminds us of this papercraft costume. The 3D video can be viewed at a remote station which uses a Kinect sensor to track your eye movements, altering the video feed’s perspective accordingly. The telepresence system also offers the ability to add in non-existent objects, making it a great tool for remote technology demonstrations and the like.
Check out the video below to see a thorough walkthrough of this 3D telepresence system.
Continue reading “Amazing 3d telepresence system”
While the Kinect is great at tracking gross body movements and discerning what part of a person’s skeleton is moving in front of the camera, the device most definitely has its shortfalls. For instance, facial recognition is quite limited, and we’re guessing that it couldn’t easily track an individual’s eye throughout the room.
No, for tracking like that, you would need something far more robust. Under the guidance of [Krystian Mikolajczyk and Jiri Matas], PhD student [Zdenek Kalal] has been working on a piece of software called TLD, which has some pretty amazing capabilities. The software uses almost any computer-connected camera to simultaneously Track an object, Learn its appearance, and Detect the object whenever it appears in the video stream. The software is so effective as you can see in the video below, that it has been dubbed “Predator”.
Once he has chosen an object within the camera’s field of vision, the software monitors that object, learning more and more about how it looks under different conditions. The software’s learning abilities allow it to pick out individual facial features, follow moving objects in video, and can recognize an individual’s face amid a collection of others.
While the software can currently only track one object at a time, we imagine that with some additional development and computing horsepower, this technology will become even more amazing.
Continue reading “Camera software learns to pick you out of a crowd”
Most people tend to enjoy a certain modicum of privacy. Aside from the data we all share willingly on the web in the form of forum posts, Twitter activity, etc., people generally like keeping to themselves.
What would you think then, if you found out your iPhone (or any iDevice with 3G) was tracking and logging your every movement?
That’s exactly what two researchers from the UK are claiming. They state that the phone is constantly logging your location using cell towers, placing the information into a timestamped database. That database is not encrypted, and is copied to your computer each time you sync with iTunes. Additionally, the database is copied back to your new phone should you ever replace your handset.
We understand that many iPhone apps use location awareness to enhance the user experience, and law enforcement officials should be able to pull data from your phone if necessary – we’re totally cool with that. However, when everywhere you have been is secretly logged in plaintext without any sort of notification, we get a bit wary. At the very least, Apple should consider encrypting the file.
While this data is not quite as sensitive as say your Social Security number or bank passwords, it is dangerous in the wrong hands just the same. Even a moderately skilled thief, upon finding or swiping an iPhone, could easily dump the contents and have a robust dataset showing where you live and when you leave – all the makings of a perfect home invasion.
Continue reading to see a fairly long video of the two researchers discussing their findings.
[Image courtesy of Engadget]
Continue reading “iPhone watching every breath you take, every move you make”