Drone Motion Capture, The Open Source Way

November 23, 2023 by Lewin Day 4 Comments

If you want to do some really advanced flying with drones, you typically need to be able to track them in space. [Joshua Bird] has whipped up a drone tracking system that can do the job for as little as $20 with millimeter-scale precision.

The system uses four PS3 Eye cameras which can be had second-hand at a cost of just $5 each. They’re modified by removing their IR cut filter, and putting in an IR-passing filter in the form of a cut-up slice of floppy disk. The system tracks the drones via their infrared indicators and the known locations of the four cameras themselves, which the system is capable of mapping out automatically. By using four cameras, the system is robust in the event the view of a camera is occluded. The system can track multiple drones at the same time, with [Joshua] demonstrating it working with two drones each carrying three infrared markers. He has the system set up to send positional updates to ESP32 microcontrollers on the drones themselves, which command the drones to hold them in set positions.

Code is available on GitHub for the curious. We’ve seen other similar work before, too.

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Open Source Tracker Keeps An Eye On Furry Friends

September 19, 2023 by Richard Baguley 49 Comments

Most of the time, you’ll know where your cats are — asleep on the bed about 23.5 hours a day and eating or pooping the rest of the time. But some cats are more active than others, so there’s commercial options for those who want to keep tabs on their pet. Unfortunately, [Sahas Chitlange] didn’t like any of them, so he designed and built his own open source version: FindMyCat.io.

The system is in two parts: a module that fits onto a cat collar, and a home station that, well, stays at home. It offers a variety of tracking modes. In home mode, the home station signals the collar every 10 seconds, which stays in a deep sleep most of the time. If the collar doesn’t get a signal from the home station, it switches to ping mode, where it will wait for a signal from the FindMyCat over the LTE-M connection and report its location.

Finally, the app can set the collar to Lost Kitteh mode, where the collar will send a location to the app every seven minutes or thirty seconds. The collar also supports a direction-finding feature, using the ultra wideband (UWB) feature of recent Apple iPhones to point you in the direction and distance of the tracked cat.

The collar is built around a Nordic Semiconductor NRF-9160, a System in a Package (SiP) that does most of the heavy lifting as it includes GPS, an LTE-M modem, and an ARM processor. One interesting feature here: [Sahas] doesn’t make his antennas on the PCB, but instead uses an Ignion NN03-310, an off-the-shelf antenna that is already qualified for LTE-M use. That means this system can be connected to almost any LTE-M network without getting yelled at for using unqualified hardware and making the local cell towers explode.

The collar also includes a DWM3001CDK ultrawideband (UWB) module used for the locator feature. The accompanying app uses this and Apple’s UWB support to show the user which direction the cat is in, and how far away it is. The app isn’t in the Apple App Store yet, so you’ll need to sign up for an Apple Developer account to use it. We’d love to hear from anyone who takes it for a test drive with their own pet.

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Smart Occupancy Sensor Knows All

March 23, 2023 by Bryan Cockfield 32 Comments

In the last few decades, building engineers and architects have made tremendous strides in improving the efficiency of various buildings and the devices that keep them safe and comfortable to live in. The addition of new technology like heat pumps is a major factor, as well as improvements on existing things like insulation methods and building materials. But after the low-hanging fruit is picked, technology like this smart occupancy sensor created by [Sina Moshksar] might be necessary to help drive further efficiency gains.

Known as RoomSense IQ, the small device mounts somewhere within a small room and uses a number of different technologies to keep track of the number of occupants in a room. The primary method is mmWave radar which can sense the presence of a person up to five meters away, but it also includes a PIR sensor to help prevent false positives and distinguish human activity from non-human activity. The device integrates with home automation systems to feed them occupancy data to use to further improve the performance of those types of systems. It’s also designed to be low-cost and easy to install, so it should be relatively straightforward to add a few to any existing system as well.

The project is also documented on this GitHub page, for anyone looking to build a little more data into their home automation system or even augment their home security systems. We imagine that devices like this could be used with great effect paired with a heating device like this, and we’ve also seen some other interesting methods of determining occupancy as well.

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Four images in one. Top left is an image of four individuals in a room with whiteboards and desks in the background along with various clutter on the floor. Over the people is a wireframe overlay of their poses. The image on the top right is just the wireframe people on a black background. Bottom left image is of a single individual standing in a room with the pose wireframe overlay. Bottom right image is the single pose wireframe on a black background.

Tracking Humans With WiFi

January 26, 2023 by Navarre Bartz 45 Comments

In case you thought that cameras, LiDAR, infrared sensors, and the like weren’t enough for Big Brother to track you, researchers from Carnegie Mellon University have found a way to track human movements via WiFi. [PDF via VPNoverview]

The process uses the signals from WiFi routers for an inexpensive way to determine human poses that isn’t hampered by lack of illumination or object occlusion. The system produces UV coordinates of human bodies by analyzing signal strength and phase data to generate a 2D feature map and then feeding that through a modified DensePose-RCNN architecture which corresponds to 3D human poses. The system does have trouble with unusual poses that are not in the training set or if there are more than three subjects in the detection area.

While there are probably applications in Kinect-esque VR Halo games, this will probably go straight into the toolbox of three letter agencies and advertising-fueled tech companies. The authors claim this to use “privacy-preserving algorithms for human sensing,” but only time will tell if they’re correct.

If you’re interested in other creepy surveillance tools, checkout the Heat-Sensing Crotch Monitor or this Dystopian Peep Show.

Hackaday Links: August 7, 2022

August 7, 2022 by Dan Maloney 10 Comments

If you ever needed proof that class-action lawsuits are a good deal only for the lawyers, look no further than the news that Tim Hortons will settle a data-tracking suit with a doughnut and a coffee. For those of you who are not in Canada or Canada-adjacent, “Timmy’s” is a chain of restaurants that are kind of the love child of a McDonald’s and a Dunkin Donut shop. An investigation into the chain’s app a couple of years ago revealed that customer location data was being logged silently, even when they were not using the app, and even far, far away from the nearest Tim Hortons. The chain is proposing to settle with class members to the tune of a coupon good for one free hot beverage and one baked good, in total valuing a whopping $8.68. The lawyers, on the other hand, will be pulling in $1.5 million plus taxes. There’s no word if they are taking that in cash or as 172,811 coffees and doughnuts, but we think we can guess.

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Bug Eliminator Zaps With A Laser

June 6, 2022 by Bryan Cockfield 26 Comments

Mosquitoes tend to be seen as an almost universal negative, at least in the lives of humans. While they serve as a food source for plenty of other animals and may even pollinate some plants, they also carry diseases like malaria and Zika, not to mention the itchy bites. Various mosquito deterrents have been invented over the years to solve some of these problems, but one of the more interesting ones is this project by [Ildaron] which attempts to build a mosquito-tracking laser.

The device uses a neural learning algorithm to identify mosquitoes flying nearby. Once a mosquito is detected, a laser is aimed at it and activated in order to “thermally neutralize” the pest. The control system as well as the neural network and machine learning are hosted on a Raspberry Pi and Jetson Nano which give it plenty of computing power. The only major downside with this specific project is that the high-powered laser can be harmful to humans as well.

Ideally, a market for devices like these would bring the price down, perhaps even through the use of something like an ASIC specifically developed for these mosquito-targeting machines. In the meantime, [Ildaron] has made this project available for replication on his GitHub page. We have also seen similar builds before which are effective against non-flying insects, so it seems like only a matter of time before there is more widespread adoption — either that or Judgement day!

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Magpies Help Each Other Escape Tracking Devices With This One Weird Trick

April 5, 2022 by Lewin Day 18 Comments

Scientists who work with animals love to track their movements. This can provide interesting insights on everything from mating behaviour, food sources, and even the way animals behave socially – or anti-socially, as the case may be.

This is normally achieved with the use of tracking devices, affixed to an animal so that it can be observed remotely while going about its normal business. However, Australian scientists have recently run into some issues in this area, as the very animals they try to track have been removing these very devices, revealing some thought-provoking behaviour in the process.

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