AWS

18 Articles

Ordering Pizza While Racing

October 9, 2023 by 6 Comments

As [Matt Stele] prepared to bike a local 300-mile (~480km) race in addition to training, he had to prepare for food. A full day of riding was ahead on gravel trails, and one of the best options for him was Casey’s General Store pizza. However, as it was a race, other riders were much faster than him. So, all the hot slices were gone when he arrived. With the help of a serverless GPS tracker, some cloud lambdas, and some good old-fashioned web scraping, [Matt] had a system that could order him a fresh pizza at the precise moment he needed. Continue reading “Ordering Pizza While Racing” →

Machine Learning Gives Cats One More Way To Control Their Humans

August 26, 2022 by 9 Comments

For those who choose to let their cats live a more or less free-range life, there are usually two choices. One, you can adopt the role of servant and run for the door whenever the cat wants to get back inside from their latest bird-murdering jaunt. Or two, install a cat door and let them come and go as they please, sometimes with a “present” for you in their mouth. Heads you win, tails you lose.

There’s another way, though: just let the cat ask to be let back in. That’s the approach that [Tennis Smith] took with this machine-learning kitty doorbell. It’s based on a Raspberry Pi 4, which lives inside the house, and a USB microphone that’s outside the front door. The Pi uses Tensorflow Lite to classify the sounds it picks up outside, and when one of those sounds fits the model of a cat’s meow, a message is dispatched to AWS Lambda. From there a text message is sent to alert [Tennis] that the cat is ready to come back in.

There’s a ton of useful information included in the repo for this project, including step-by-step instructions for getting Amazon Web Services working on the Pi. If you’re a dog person, fear not: changing from meows to barks is as simple as tweaking a single line of code. And if you’d rather not be at the beck and call of a cat but still want to avoid the evidence of a prey event on your carpet, machine learning can help with that too.

[via Tom’s Hardware]

Comfortable, wearable packaging for biometric device for monitoring physiological data and pushing the data to the cloud

A DIY Biometric Device With Some Security Considerations

December 11, 2021 by 8 Comments

Biohacking projects are not new to Hackaday and it’s certainly a genre that really piques our interest. Our latest biohacking device comes courtesy of [Manivannan] who brings his flavor of a wearable biosensor with some security elements built-in through AWS.

The hardware is composed of some impressive components we have seen. He has an AD8232 electrocardiogram front end, the MAX30102 integrated pulse oximeter IC for determining blood oxygen and heart rate, and the ever-popular LM35 for measuring body temperature. Either of these chips would be perfect for your next DIY biosensor project though you might try the MAX30205 body temperature sensor given its 0.1-degree Celsius accuracy. However, what really piqued our interest was the use of Microchip’s AVR-IoT WA Development Board. Now we’ve talked about this board before and also mentioned you could probably do all the same things with an ESP-device, but perhaps now we get to see the board a bit more in action.

[Manivannan] walks the reader through the board’s setup and everything looks to be pretty straightforward. He ultimately rigged together a very primitive dashboard for viewing all his vitals in real-time, demonstrating how you could put together your own patient dashboard for remote monitoring of vitals or other sensor signals. He emphasizes that all this is powered through AWS, giving him some added security layers that are critical for protecting his data from unwanted viewers.

Though [Manivannan’s] security implementation doesn’t rise to the standard of medical devices, maybe it will serve as a case study in the growing open-source medical device movement.

Continue reading “A DIY Biometric Device With Some Security Considerations” →

If Coffee == True {

March 7, 2020 by 14 Comments

Having a shared coffee maker in the workplace is both a blessing and a curse. It’s nice to have constant access to coffee, but it can be frustrating to find the coffee pot emptied right as you walk in to the break room. To solve this problem in their office, [Vitort] and co. built an IOT solution that notifies everyone of the current coffee status on a Slack channel.

This project wasn’t built just as a convenience for the office, either. It makes extensive use of AWS SNS, the simple notification system from Amazon Web Services because they wanted to learn to use this technology specifically. Besides the notification system, the device itself is based on a NodeMCU/ESP8266, communicating over WiFi, and is a simple push-button design which coffee drinkers push when a fresh pot is made, and then push again when the coffee is empty.

While relatively straightforward, this project is a good one to look at if you’ve been interested in AWS at all, especially the simple notification system. It’s a pretty versatile tool, and all of the code used in the project is available on the project page for your reading pleasure. If you’re more interested in the coffee aspect of this project, we have a special coffee maker for you too.

Train All The Things Contest Update

March 3, 2020 by 2 Comments

Back in January when we announced the Train All the Things contest, we weren’t sure what kind of entries we’d see. Machine learning is a huge and rapidly evolving field, after all, and the traditional barriers that computationally intensive processes face have been falling just as rapidly. Constraints are fading away, and we want you to explore this wild new world and show us what you come up with.

Where Do You Run Your Algorithms?

To give your effort a little structure, we’ve come up with four broad categories:

  • Machine Learning on the Edge
    • Edge computing, where systems reach out to cloud resources but run locally, is all the rage. It allows you to leverage the power of other people’s computers the cloud for training a model, which is then executed locally. Edge computing is a great way to keep your data local.
  • Machine Learning on the Gateway
    • Pi’s, old routers, what-have-yous – we’ve all got a bunch of devices laying around that bridge space between your local world and the cloud. What can you come up with that takes advantage of this unique computing environment?
  • Machine Learning in the Cloud
    • Forget about subtle — this category unleashes the power of the cloud for your application. Whether it’s Google, Azure, or AWS, show us what you can do with all that raw horsepower at your disposal.
  • Artificial Intelligence Blinky
    • Everyone’s “hardware ‘Hello, world'” is blinking an LED, and this is the machine learning version of that. We want you to use a simple microprocessor to run a machine learning algorithm. Amaze us with what you can make an Arduino do.

These Hackers Trained Their Projects, You Should Too!

We’re a little more than a month into the contest. We’ve seen some interesting entries bit of course we’re hungry for more! Here are a few that have caught our eye so far:

  • Intelligent Bat Detector – [Tegwyn☠Twmffat] has bats in his… backyard, so he built this Jetson Nano-powered device to capture their calls and classify them by species. It’s a fascinating adventure at the intersection of biology and machine learning.
  • Blackjack Robot – RAIN MAN 2.0 is [Evan Juras]’ cure for the casino adage of “The house always wins.” We wouldn’t try taking the Raspberry Pi card counter to Vegas, but it’s a great example of what YOLO can do.
  • AI-enabled Glasses – AI meets AR in ShAIdes, [Nick Bild]’s sunglasses equipped with a camera and Nano to provide a user interface to the world. Wave your hand over a lamp and it turns off. Brilliant!

You’ve got till noon Pacific time on April 7, 2020 to get your entry in, and four winners from each of the four categories will be awarded a $100 Tindie gift card, courtesy of our sponsor Digi-Key. It’s time to ramp up your machine learning efforts and get a project entered! We’d love to see more examples of straight cloud AI applications, and the AI blinky category remains wide open at this point. Get in there and give machine learning a try!

Behind Amazon’s Doors Is A Library

December 6, 2019 by 7 Comments

Some people love Amazon, while others think it has become too big and invasive. But you have to admit, they build gigantic and apparently reliable systems. Interestingly, they recently released a library of white papers from their senior staff called the Builder’s Library.

According to their blog post:

The Amazon Builders’ Library is a collection of living articles that take readers under the hood of how Amazon architects, releases, and operates the software underpinning Amazon.com and AWS. The Builders’ Library articles are written by Amazon’s senior technical leaders and engineers, covering topics across architecture, software delivery, and operations. For example, readers can see how Amazon automates software delivery to achieve over 150 million deployments a year or how Amazon’s engineers implement principles such as shuffle sharding to build resilient systems that are highly available and fault tolerant.

The Amazon Builders’ Library will continue to be updated with new content going forward.

Continue reading “Behind Amazon’s Doors Is A Library” →