The Heat Of The Moments – Location Visualization In Python

Have you ever taken a look at all the information that Google has collected about you over all these years? That is, of course, assuming you have a Google account, but that’s quite a given if you own an Android device and have privacy concerns overruled by convenience. And considering that GPS is a pretty standard smartphone feature nowadays, you shouldn’t be surprised that your entire location history is very likely part of the collected data as well. So unless you opted out from an everchanging settings labyrinth in the past, it’s too late now, that data exists — period. Well, we might as well use it for our own benefit then and visualize what we’ve got there.

Location data naturally screams for maps as visualization method, and [luka1199] thought what would be better than an interactive Geo Heatmap written in Python, showing all the hotspots of your life. Built around the Folium library, the script reads the JSON dump of your location history that you can request from Google’s Takeout service, and overlays the resulting heatmap on the OpenStreetMap world map, ready for you to explore in your browser. Being Python, that’s pretty much all there is, which makes [Luka]’s script also a good starting point to play around with Folium and map visualization yourself.

While simply just looking at the map and remembering the places your life has taken you to can be fun on its own, you might also realize some time optimization potential in alternative route plannings, or use it to turn your last road trip route into an art piece. Just, whatever you do, be careful that you don’t accidentally leak the location of some secret military facilities.

[via r/dataisbeautiful]

SatNOGS Update Hack Chat

Join us on Wednesday, October 30 at noon Pacific for the SatNOGS Update Hack Chat with Pierros Papadeas and the SatNOGS team!

Ever since the early days of the Space Race, people have been fascinated with satellites. And rightly so; the artificial moons we’ve sent into orbit are engineering marvels, built to do a difficult job while withstanding an incredibly harsh environment. But while most people are content to just know that satellites are up there providing weather forecasts and digital television, some of us want a little more.

Enter SatNOGS. Since winning the very first Hackaday Prize in 2014, SatNOGS has grown into exactly what Pierros Papadeas and the rest of the team envisioned: a globe-spanning network of open-source satellite ground stations, feeding continuous observations into an open, accessible database. With extensive documentation and an active community, SatNOGS has helped hundreds of users build ground stations with steerable antennas and get them connected. The network tracks hundreds of Low-Earth Orbit (LEO) satellites each day, including increasingly popular low-cost Cubesats.

Join us as the SatNOGS crew stops by the Hack Chat to give us an update on their efforts over the last few years. We’ll discuss how winning the Hackaday Prize changed SatNOGS, how the constellation of satellites has changed and how SatNOGS is dealing with it, and what it takes to build a global network and the community that makes it work.

join-hack-chatOur Hack Chats are live community events in the Hackaday.io Hack Chat group messaging. This week we’ll be sitting down on Wednesday, October 30 at 12:00 PM Pacific time. If time zones have got you down, we have a handy time zone converter.

Click that speech bubble to the right, and you’ll be taken directly to the Hack Chat group on Hackaday.io. You don’t have to wait until Wednesday; join whenever you want and you can see what the community is talking about.

Keep Pesky Cats At Bay With A Machine-Learning Turret Gun

It doesn’t take long after getting a cat in your life to learn who’s really in charge. Cats do pretty much what they want to do, when they want to do it, and for exactly as long as it suits them. Any correlation with your wants and needs is strictly coincidental, and subject to change without notice, because cats.

[Alvaro Ferrán Cifuentes] almost learned this the hard way, when his cat developed a habit of exploring the countertops in his kitchen and nearly turned on the cooktop while he was away. To modulate this behavior, [Alvaro] built this AI Nerf turret gun. The business end of the system is just a gun mounted on a pan-tilt base made from 3D-printed parts and a pair of hobby servos. A webcam rides atop the gun and feeds into a PC running software that implements the YOLO3 localization algorithm. The program finds the cat, tracks its centroid, and swivels the gun to match it. If the cat stays in the no-go zone above the countertop for three seconds, he gets a dart in his general direction. [Alvaro] found that the noise of the gun tracking him was enough to send the cat scampering, proving that cats are capable of learning as long as it suits them.

We like this build and appreciate any attempt to bring order to the chaos a cat can bring to a household. It also puts us in mind of [Matthias Wandel]’s recent attempt to keep warm in his shop, although his detection algorithm was much simpler.

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Motion Tracking Face Really Does Follow You Around The Room

Many of us have had the experience of viewing an artwork in a gallery, in which the eyes appear to follow one around the room. In our high-technology work, this no longer need be achieved with artistic skill. You can just build something that actually moves instead.

Chartreuse is the creation of [alynton], and has a personality all its own. A face was created out of laser cut wood, and assembled layer by layer. It was then given glowing LED eyes, and mounted on a rotating plate. Combined with an Arduino and an ultrasonic sensor, it’s capable of tracking targets moving within its field of view, and rotating to follow them. Chartreuse’s expression changes as well, with from happy to forlorn, depending on the situation.

It’s a great example of the artistic results that can be achieved by layering lasercut materials, as well as how art can be brought to life with simple maker staples like servos and microcontrollers. Motion tracking has plenty of useful applications, too – like aiming heat directly at cold humans. Video after the break.

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Wandel Weaponizes Waste With Lego And A Raspberry Pi

Before 3D printers, there was LEGO. And the little bricks are still useful for putting something together on the quick. Proof is YouTuber [Matthias Wandel]’s awesome bottle cap shooter build that uses rudimentary DIY computer vision to track you and then launch a barrage of plastic pieces at you.

This is an amazing project that has a bit of something for everyone. Lets start with the LEGO. [Matthias Wandel] starts with making a crossbow designed launcher and does an awesome job with showing us how it works in a video. The mechanism is an auto reloading and firing system that can be connected to a stepper motor. Next comes the pan and tilt mechanism which allows the turret to take better aim at moving targets: more LEGO and stepper motors.

The target tracker uses color matching in a program that curiously uses no OpenCV. It compares consecutive frame and then filters out red objects – the largest red dot is it. Since using a fisheye lens on the Raspbery Pi camera adds distortion, [Matthias Wandel] uses a jig made with more Legos to calibrate the image.

The final testing involved having his own child walk around the room being hunted but the autonomous machine. Kids do love toys even if they are trying to shoot bottle caps at them.

Want more Lego inspiration? Check out the Lego Quadcopter Mod and the Lego Tank with the ESP8266.

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Raspberry Pi Tracks Humans, Blasts Them With Heat Rays

Given how long humans have been warming themselves up, you’d think we would have worked out all the kinks by now. But even with central heating, and indeed sometimes because of it, some places we frequent just aren’t that cozy. In such cases, it often pays to heat the person, not the room, but that can be awkward, to say the least.

Hacking polymath [Matthias Wandel] worked out a solution to his cold shop with this target-tracking infrared heater. The heater is one of those radiant deals with the parabolic dish, and as anyone who’s walked past one on demo in Costco knows, they throw a lot of heat in a very narrow beam. [Matthias] leveraged a previous project that he whipped up for offline surveillance as the core of the project. Running on a Raspberry Pi with a camera, the custom software analyzes images and locates motion across the width of a frame. That drives a stepper that swivels a platform for the heater. The video below shows the build and the successful tests; however, fans of [Matthias] should prepare themselves for a shock as he very nearly purchases a lazy susan to serve as the base for the heater rather than building one.

We’re never disappointed by [Matthias]’ videos, and we’re always impressed by his range as a hacker. From DIY power tools to wooden logic circuits to his recent Lego chocolate engraver, he always finds ways to make things interesting.

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Super Simple, Super Cheap FPV Drone Tracking

What’s more disruptive to the drone first-person view (FPV) experience than dropouts in your video feed when you’re in the middle of a race? Probably nothing, and there’s probably also not much you can do about it. Or is there? Might a simple tracker based on RSSI help keep your video signal locked in?

Honestly, we’re not sure it would, but we think it’s pretty nifty to see [FlyerFpv]’s tracker following his drone around. The idea is simple and uses the full-diversity FPV receiver he already has. Diversity receivers constantly monitor signal strength from multiple antennas to determine which one to listen to, which improves reception quality. [FlyerFpv] sends the RSSI outputs to analog inputs on an Arduino which drives a servo to keep the signals as close to each other as possible. The Arduino and the DC-DC converter needed to power it fit nicely inside the receiver case with no modifications, which is a nice touch. With a 3D-printed servo mount and some fancy directional antennas, the setup keeps pretty good track of his drone now. See it in action below.

Sure, the response could be snappier, and we’d love to see another receiver and servo added to track pitch as well as yaw. For a first pass, we think it’s great, but [FlyerFpv] should enjoy it while he can in case AI takes over our flying fun soon.

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