Action cameras like the GoPro, and the Sony Action Cam are invaluable tools for cyclists and anyone else venturing into the great outdoors. These cameras are not really modifiable or usable in any way except for what they were designed for. [Connor] wanted a cheaper, open-source action camera and decided to build one with the Raspberry Pi.
[Connor]’s Pi action cam is built around the Raspberry Pi Model A+ and the Pi camera. This isn’t a complete solution, so [Connor] added a bluetooth module, a 2000 mAh battery, and a LiPo charger.
To keep the Pi Action Cam out of the elements, [Connor] printed an enclosure. It took a few tries, but eventually he was able to mount everything inside a small plastic box with buttons to start and stop recording, a power switch, and a USB micro jack for charging the battery. The software is a script by [Alex Eames], and the few changes necessary to make this script work with the hardware are also documented.
This was the most intensive 3D printing project [Connor] has ever come up with, and judging by the number of prints that don’t work quite right, he put a lot of work into it. Right now, the Pi action cam works, but there’s still a lot of work to turn this little plastic box into a completed project.
If you live out in the boondocks, out of reach from the Google Maps car, you might have noticed there aren’t too many pictures of your area on the Internet. Mapillary is hoping to change that with crowdsourced photos of the entire planet, with mobile apps that snap a pic and upload it to the web. [sabas1080] is bringing this capability to the most popular ARM dev board out there, the Raspberry Pi.
The Raspberry Pi is not a phone, the usual way to upload pics to Mapillary. There’s no GPS, so geotagging is out of the question. The Pi doesn’t have a camera or a screen, and if you’re taking pictures of remote locations, a battery would be a good idea.
All these pieces are available for the Pi, though; [sabas1080] sourced a display from Adafruit, the camera is a standard Raspi affair, and the GPS is a GY-NEO6MV2 module from the one of the numerous Chinese retailers. Add a big power bank battery, and all the hardware is there.
The software is where this build gets tricky. Mapillary has a nice set of free tools written in Python, no less, but this is only part of the build. [sabas1080] needed to connect the camera, set up the display, and figure out how to make everything work with the Mapillary tools. In the end, [sabas] was able to get the entire setup working as a programmable, mobile photo booth.
[James J. Guthrie] just published a rather formal announcement that his 4-node Raspberry Pi cluster greatly outperforms a 64-node version. Of course the differentiating factor is the version of the hardware. [James] is using the Raspberry Pi 2 while the larger version used the Model B.
We covered that original build almost three years ago. It’s a cluster called the Iridris Pi supercomputer. The difference is a 700 MHz single core versus the 900 Mhz quad-core with double-the ram. This let [James] benchmark his four-node-wonder at 3.048 gigaflops. You’re a bit fuzzy about what a gigaflops is exactly? So were we… it’s a billion floating point operations per second… which doesn’t matter to your human brain. It’s a ruler with which you can take one type of measurement. This is triple the performance at 1/16th the number of nodes. The cost difference is staggering with the Iridris ringing in at around £2500 and the light-weight 4-node built at just £120. That’s more than an order of magnitude.
Look, there’s nothing fancy to see in [James’] project announcement. Yet. But it seems somewhat monumental to stand back and think that a $35 computer aimed at education is being used to build clusters for crunching Ph.D. level research projects.
Back in 1988 [Ben Reardon] walked through the Japanese pavilion at the World Expo held in Brisbane, Australia. He saw a robot playing a classical guitar, and was in awe. Later in his life, he decided to learn guitar, and always thought back to that robot. After going to SIGGRAPH 2014 and being inspired by all the creative makers out there, he realized the technology was here — to build his own Robot Guitar.
He started small though — with a prototype robotic Tambourine. It helped flush out some of the ideas for coding that he would eventually employ on the Robot Guitar. The guitar features both an Arduino and a Raspberry Pi, along with six RC servos — one for each string. The biggest challenge with the project was getting the servos mounted just right — stiff, but with adjustment so each pick could be tuned for identical timing. He ended up using aluminum extrusion to mount the servos, three per side in order to leave space for the picks.
Once the mechanical portion was done — onto the coding…
In the end, it ended up being only 460 lines of code. Python and a bit of Bash for the Raspberry Pi — and of course a few sketches for the Arduino. But enough talking about it — let’s hear it!
Continue reading “Robotic Player Guitar Rocks Out on Its Own”
A while ago, [Kyle] built an automated mushroom cultivator. This build featured a sealed room to keep contaminants out and enough air filtering and environmental controls to produce a larger yield of legal, edible mushrooms than would otherwise normally be possible.
Now, he’s at it again. He’s expanded the hardware of his build with a proper, grounded electrical box for his rig, added more relays, implemented PID for his temperature and humidity controller, and greatly expanded the web interface for his fungiculture setup.
Like the previous versions of his setup, this grow chamber is controlled by a Raspberry Pi with a camera and WiFi module. Instead of the old plastic enclosure, [Kyle] is stepping things up with a proper electrical enclosure, more relays, more humidity and temperature sensors, and a vastly improved software stack. Inside the enclosure are eight relays for heaters and humidifiers. The DHT22 sensors around the enclosure are read by the Pi, and with a proper PID control scheme, controlling both the temperature and humidity is simply a matter of setting a number and letting the machine do all the work.
The fungi of [Kyle]’s labor include some beautiful pink and white oyster mushrooms, although with a setup like this there’s not much fungiculture he can’t do.
We’re not sure if the Chickens know it yet, but they could be one of the reasons for all this IoT craze now a days. Look for chicken coop, and out come dozens of posts from the Hackaday chest.
Here’s another one from self confessed lazy engineer [Eric]. He didn’t want to wake up early to let his chickens out in the morning, or walk out to the coop to lock them up for the night to protect them from predators like Foxes, Raccoons and Opossum. So he built a Raspberry-Pi controlled chicken coop door that automates locking and unlocking. The details are clear from his video which you can watch after the break. The door mechanism looks inspired from an earlier anti-Raccoon gravity assist door.
The hardware (jpg image) is simple – a couple of hall sensors that detect the open/close status of the coop door that is driven by a DC motor via a bridge controller. The whole setup is controlled using a Raspberry-Pi and this is where the fun starts – because he can now add in all kinds of “feature creep”. Motion sensor, camera, light array, and anti-predator gizmos are all on his drawing board at the moment. Add in your feature requests in the comments below and let’s see if [Eric] can build the most advanced, complicated, gizmo filled chicken coop in the Universe. Combine that with this design, and it could even turn out to be the most beautiful too.
Continue reading “Raspberry Pi Controlled Chicken Door”
If you are interested in local wildlife, you may want to consider this wildlife camera project (Google cache). [Arnis] has been using his to film foxes and mice. The core components of this build are a Raspberry Pi and an infrared camera module specifically made for the Pi. The system runs on a 20,000 mAh battery, which [Arnis] claims results in around 18 hours of battery life.
[Arnis] appears to be using a passive infrared (PIR) sensor to detect motion. These sensors work by detecting sudden changes in the amount of ambient infrared radiation. Mammals are good sources of infrared radiation, so the sensor would work well to detect animals in the vicinity. The Pi is also hooked up to a secondary circuit consisting of a relay, a battery, and an infrared light. When it’s dark outside, [Arnis] can enable “night mode” which will turn on the infrared light. This provides some level of night vision for recording the furry critters in low light conditions.
[Arnis] is also using a Bluetooth dongle with the Pi in order to communicate with an Android phone. Using a custom Android app, he is able to connect back to the Pi and start the camera recording script. He can also use the app to sync the time on the Pi or download an updated image from the camera to ensure it is pointed in the right direction. Be sure to check out the demo video below.
If you like these wildlife cameras, you might want to check out some older projects that serve a similar purpose. Continue reading “Remote Controlled Wildlife Camera with Raspberry Pi”