Identifying Creatures That Go Chirp In The Night

It’s common knowledge that bats navigate and search for their prey using echolocation, but did you know that the ultrasonic chips made by different species of bats are distinct enough that they can be used for identification? [Tegwyn☠Twmffat] did, which is why he came up with this impressive device capable of cataloging the different bats flying around at night.

Now this might seem like an odd gadget to have, but if you’re in the business of wildlife conservation, it’s not hard to imagine how this sort of capability might be useful. This device could be used to easily estimate the size and diversity of bat populations in a particular area. [Tegwyn☠Twmffat] also mentions that, at least in theory, the core concept should work with other types of noisy critters like rodents or dolphins.

Powered by the NVIDIA Jetson Nano, the unit listens with a high-end ultrasonic microphone for the telltale chirps of bats. These are then processed by the software and compared to a database of samples that [Tegwyn☠Twmffat] personally collected in local nature reserves. In the video after the break, you can also see how he uses a set of house keys jingling as a control to make sure the system is running properly.

As winner of the Train All the Things contest back in April, we’re eager to see how the Intelligent Wildlife Species Detector will fare as the competition heats up in the 2020 Hackaday Prize.

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Approaching The Drop Location: Seeds Away!

Arbor Day is a holiday many countries dedicate to planting trees, but with the steady encroachment of climate change, we need to maximize our time. Dronecoria doesn’t just plant a tree; it sows “hectares in minutes.” A hectare is 10,000 square meters or 2.471 acres. These aren’t the drones you’re looking for if you intend a weekend of gardening, this is in the scope of repopulating a forest with trees or reinvigorating a park with wildflowers. The seed balls in the hopper are 10kg of native seeds coupled with beneficial microorganisms to help the chances of each drop.

The drone’s body is laser cut from what looks like baltic birch plywood. The vector files are available in Illustrator (.ai) and CAD (.dxf) formats released under Creative Commons BY-SA, so give credit if you redistribute or remix it. In the 3D realm, you’ll need a SeedShutter and SeedDisperser, and both models are available in STL format.

We have other non-traditional seed spreading methods like canons, but it is a big job, and if you’ve build something to pitch in, drop us a tip!

Auto-Tracking Sentry Gun Gives Deer A Super Soaking

Things rarely go well when humans mix with wildlife. The problems are exacerbated in the suburbs, where bears dine on bird feeders and garbage cans, raccoons take up residence in attics, and coyotes make off with the family cat. And in the suburbs, nuisance wildlife can be an intractable problem because the options for dealing with it are so limited.

Not to be dissuaded in the battle to protect his roses, [dlf.myyta] built this motion-activated sentry gun to apply some watery aversion therapy to marauding deer. Shown in action below against a bipedal co-conspirator, the sentry gun has pretty much what you’d expect under the hood — Raspberry Pi, NoIR camera, a servo for aiming and a solenoid valve to control the water. OpenCV takes care of locating the intruders and swiveling the nozzle to center mass; since the deer are somewhat constrained by a fence, there’s no need to control the nozzle’s elevation. Everything is housed nicely in a plastic ammo can for portability and waterproofing. Any target that stands still for more than three seconds gets a hosing; we assume this is effective, but alas, no snuff films were provided.

We’re not sure if [dlf.myyta]’s code can discern friend from foe, and in this litigious world, hosing the neighbor’s kid could be a catastrophe. Perhaps version 2.0 can include image recognition for target verification.

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Hackaday Prize Entry: Automated Wildlife Recognition

Trail and wildlife cameras are commonly available nowadays, but the Wild Eye project aims to go beyond simply taking digital snapshots of critters. [Brenda Armour] uses a Raspberry Pi to not only take photos of wildlife who wander into the camera’s field of view, but to also automatically identify and categorize the animals seen using a visual recognition API from IBM via the Node-RED infrastructure. The result is a system that captures an image when motion is detected, sends the image to the visual recognition API, and attempts to identify any wildlife based on the returned data.

The visual recognition isn’t flawless, but a recent proof of concept shows promising results with crows, a cat, and a dog having been successfully identified. Perhaps when the project is ready to move deeper into the woods, elements from these solar-powered networked birdhouses (which also use the Raspberry Pi) could help cut some cords.

Hackaday Prize Entry : DEER — An Electronic Repellent

Ultrasonic repellent devices used to keep away insects, rodents, birds, and even large animals have been around for quite a while, but their effectiveness depends on who you ask.  Some critters just don’t seem affected, while some others definitely will avoid being around such a device. Deploying a few of these devices to scare off animals seems to be working quite well for [Ondřej Petrlík]. Around where he lives, the fields of tall grass need to be mowed down during the spring. Unfortunately, the tall grass is ideal for young, newborn animals to stay hidden and safe. The mowing machines would often cripple and hurt such animals, and [Ondřej] desperately wanted to solve the problem and prevent these mishaps.

He built an electronic repeller to keep away wild animals and their young from his farm/ranch/range back in the Czech Republic. He used an Arduino Mini to drive a large piezo transducer to scare away the wild animals from the vicinity of the device. He likely used a high enough frequency beyond human range, but we’ll know more when he publishes his code and details. There are also a few large 10mm LED’s – either to visually locate the device or help drive the animals away in conjunction with the ultrasound, with an LDR that activates the LEDs at night. Using the Arduino helps to turn on the transducer at random intervals, and hopefully, he is using a range of different frequencies so the animals don’t become immune to the device.

His first prototype was cobbled together using vanilla, off the shelf parts. An Arduino, a step up converter, an LDR, a couple of LEDs, a reed switch for powering it on via a magnet, and a large ultrasonic transducer, all powered by three alkaline AA batteries. He stuffed it all inside a weatherproof molded enclosure, holding it all together with a lot of hot glue. This didn’t make it very rugged for the long-term, outdoor field use. While the prototype worked well, he needed several of the devices to be placed all around his farm. To make assembly easy and make it more reliable, he designed a custom PCB to fit in the weather proof enclosure. This allowed him to easily mount all the required parts for a more reliable result. His project is still a work in progress, so if you have worked with these types of ultrasonic repellent devices to keep away animals, and have any insights that may help him, do chime in with your comments. [Ondřej] seems pretty satisfied with the results so far.

A Field Guide To The North American Communications Tower

The need for clear and reliable communication has driven technology forward for centuries. The longer communication’s reach, the smaller the world becomes. When it comes to cell phones, seamless network coverage and low power draw are the ideals that continually spawn R&D and the eventual deployment of new equipment.

Almost all of us carry a cell phone these days. It takes a lot of infrastructure to support them, whether or not we use them as phones. The most recognizable part of that infrastructure is the communications tower. But what do you know about them?

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Wildlife Camera

Remote Controlled Wildlife Camera With Raspberry Pi

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”