Laundry. It’s one of life’s inescapable cycles, but at least we have machines now. The downside of this innovation is that since we no longer monitor every step — the rock-beating, the river-rinsing, the line-hanging and -retrieving — the pain of laundry has evolved into the monotony of monitoring the robots’ work.
[Adam] shares his wash-bots with roommates, and they aren’t close enough to combine their lights and darks and turn it into a group activity. They needed an easy way to tell when the machines are done running, and whose stuff is even in there in the first place, so [Adam] built a laundry machine monitor that uses current sensing to detect when the machines are done running and sends a text to the appropriate person.
Each machine has a little Hall effect-sensing module that’s carefully zip-tied around its power cable. The signal from these three-wire boards goes high when the machine is running and low when it’s not. At the beginning of the load, the launderer simply presses their assigned button on the control box, and the ESP32 inside takes care of the rest.
Getting a text when your drawers are clean is about as private as it gets. Clean underwear, don’t care? Put it on a scrolling marquee.
If you live in a bustling city and have anyone over who drives, it can be difficult for them to find parking. Maybe you have an assigned space, but they’re resigned to circling the block with an eagle eye. With those friends in mind, [Adam Geitgey] wrote a Python script that takes the video feed from a web cam and analyzes it frame by frame to figure out when a street parking space opens up. When the glorious moment arrives, he gets a text message via Twilio with a picture of the void.
It sounds complicated, but much of the work has already been done. Cars are a popular target for machine learning, so large data sets with cars already exist. [Adam] didn’t have to train a neural network, either–he found a pre-trained Mask R-CNN model with data for 80 common objects like people, animals, and cars.
The model gives a lot of useful info, including a bounding box for each car with pixel coordinates. Since the boxes overlap, there needs be a way to determine whether there’s really a car in the space, or just the bumpers of other cars. [Adam] used intersection over union to do this, which is conveniently available as a function of the Mask R-CNN model’s library. The function returns a score, so it was just a matter of ignoring low-scoring bounding boxes.
[Adam] purposely made the script adaptable. A few changes here and there, and you could be picking up tennis balls with a robotic collector or analyzing human migration patterns on your block in no time. Or change it up and detect all the cars that run the stop sign by your house.
Thanks for the tip, [foamyguy].
In these turbulent times, journalists fearmonger and honest citizens fear for the safety of their homes and themselves. Adding some security features can allay these fears, and with the advent of cheap technology, front door cameras have become popular. There’s a wide array of options on the market, but short of watching hours of logged video, they’re not always super useful. Adding some smarts can really help – as [Peter Quinn] has done.
For this project, [Peter] decided on a JeVois smart camera. More than just a USB webcam, it also packs a quad-core processor running machine vision algorithms. This allows object recognition and other tasks to be run on the camera itself. In this setup, [Peter] configured the JeVois camera to detect people. When a human is detected upon the doorstep, the camera sends a message to the connected Raspberry Pi over serial. The Raspberry Pi then captures a JPEG still from the camera over the USB connection, and, using Twilio, sends a notification to [Peter]’s phone.
It’s a well-integrated system that automatically photographs visitors to [Peter]’s home, requiring little to no interaction from the user. We’ve seen other integrated machine vision platforms, too – such as the OpenMV, which got its start as a Hackaday Prize entry, way back in 2017.
When Python was created, [Guido van Rossum] knew that one day it would be fully realized and take its final form. Clearly, that day has arrived since there now exists a way to send a word query and receive a lengthy list of potential portmanteaus. Some may regard this as merely quaint, but it will be the most important thing to happen in binary until the singularity.
Perhaps we are overpromising a smidge, but it may be fun to spend an afternoon getting your own whimsicalibrated pun resource churning out some eye-roll-worthy word combos. The steps are broken up neatly and explained at a high level with links for more in-depth explanations so a novice can slog through it, but a whiz can wrap it up while the boss is looking the other way.
We truly live in the future, but we may continue writing our own brand of artisanal puns which are number one in someone’s book.
If you have not had children, stop reading now, we implore you. Because before you’ve had kids, you can’t know how supremely important it is that they take care of going to the bathroom by themselves. [David Gouldin] knows how it is. But unlike most of us, he resorted to using an Amazon IoT button and Twilio. No, we are not kidding.
The problem he was trying to solve is when his younger child would need to use the potty in the middle of the night, calling out for assistance would wake the older child. [David] said it best himself:
Behind the smiling emoji facade is an Amazon IoT button, a variant of Amazon’s dash button. When my kid presses this button, it triggers an AWS Lambda function that uses Twilio’s Python Helper Library to call my iPhone from a Twilio number. The Twilio number is stored in my contacts with “emergency bypass” turned on, so even when it’s 2am and I’m on “do not disturb” I still get the call.
Continue reading “IoT Potty Training”
When you move you generally load up everything you own into one truck. If your entire life is ever going to get ripped off, this is probably when it’s going to happen. To guard against the threat [Tim Flint] built his own alarm for a moving truck. If someone opens the door on the truck it’ll alert him via text message. Hopefully he’s got an annoying notification sound that will wake him up in time to catch them red-handed.
The setup is simple and shouldn’t distract you too much from your packing and loading. [Tim] connected a proximity sensor to an Arduino board which has its own WiFi module. The entire thing is housed in the black project box seen above and the proximity sensor is pointed at the moving truck door. When the door is opened the Arduino pushes an alert to Twilio which is configured to send him text messages.
The alarm system doesn’t protect from someone stealing the entire truck… that kind of system is an entirely different project.