Alfred Jones And Kipp Bradford To Deliver Keynotes At Remoticon Next Week

There’s just one week left until Hackaday Remoticon, our online gathering in place of our traditional in-person conference during this time of social distancing. Joining the more than 20 hands-on workshops that make up the bulk of Remoticon, we’re excited to announce the two keynote speakers who will be taking the virtual stage: Alfred Jones and Kipp Bradford.

Tickets to see these keynote talks, to watch the SMD Challenge, to see hardware demos, and to take part in the show and tell are free, so get yours today!

 

Alfred Jones

Alfred Jones

Head of Mechanical Engineering at Lyft’s Self-Driving Division

Alfred Jones is the Head of Mechanical Engineering at Lyft’s level 5 self-driving division. Level 5 means there are no humans involved in operating the vehicle and it is still capable of driving anywhere a human could have. What goes into modifying a vehicle for this level of self-driving? What processes does his team use to deliver safe automation? And will cars in the near future completely get rid of the driver’s seat? Alfred knows and we’ll be hanging on his every word!

Kipp BradfordKipp Bradford

CTO fo Treau

Kipp Bradford is the CTO of Treau, a company bringing heating, ventilation, and air conditioning (HVAC) into the information age. These systems contribute as much as 20% of global emissions each year, so even small efficiency gains stand to have a huge impact. The industry has remained nearly unchanged for decades, and Kipp is at the forefront of evolving the hidden systems found in nearly every building. Will the air conditioner of tomorrow make the one we have today look like a rotary telephone? We look forward to hearing what Kipp has to say about it.

We’re so excited to have these two phenomenal speakers who have also both been involved as expert judges in the Hackaday Prize (Alfred in 2020, Kipp in 2017 and 2018). Help us show our appreciation by packing the virtual lecture halls for their talks on Saturday, November 7th! Get your free ticket now.

Automation With A New Twist

Turning on a lightbulb has never been easier. You can do it from your mobile. Voice activation through home assistants is robust. Wall switches even play nicely with the above methods. It was only a matter of time before someone decided to make it fun, if you consider a Rubik’s cube enjoyable. [Alastair Aitchison] at Playful Technology demonstrated that it is possible to trigger a relay when you match all the colors. Video also after the break.

The cube does little to obfuscate game data, so in this scope, it sends unencrypted transmissions. An ESP32 with [Alastair]’s Arduino code, can track each movement, and recognize a solved state. In the video, he solves the puzzle, and an actuator releases a balloon. He talks about some other cool things this could do, like home automation or a puzzle room, which is in his wheelhouse judging by the rest of his YouTube channel.

We would love to see different actions perform remote tasks. Twisting the top could set a timer for 1-2-3-4-5 minutes, while the bottom would change the bedroom lights from red-orange-yellow-green-blue-violet. Solving the puzzle should result in a barrage of NERF darts or maybe keep housemates from cranking the A/C on a whim.

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Building The Ultimate Raspberry Pi Automation Controller

At this point, we’ve lost count of how many automation projects we’ve seen with some variant of a Raspberry Pi at the helm. Which is hardly surprising, as the boards are cheap, powerful, and well documented. The list of reasons not to use one has never been very long, but with the PiCon One that [Frank] has been working on, it’s about to get even shorter.

The project takes the form of an IP65 industrial enclosure and support electronics that the Raspberry Pi Zero W plugs into. While expandable in nature, [Frank] has a core set of features he’s aiming for as a baseline such as additional serial ports, integrated uninterruptible power supply, a battery-backed Real Time Clock (RTC), an array of programmable status LEDs, and support for XBee and GPS plug-in modules. Feedback is provided through a pair of four digit seven-segment displays and a color 320×480 TFT screen running a custom user interface.

[Frank] envisions the PiCon One for use as a rugged solar power controller, eventually able to measure array output, energy consumption, and even operate motorized mounts to keep the panels pointed at the sun. To that end, he’s recently been experimenting with running JPL’s Horizon software on the Pi to determine the sun’s position in real-time. But the device is capable of so much more, and would make an ideal controller for many home and potentially even industrial applications.

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Automating Mini Blinds The Rental-Friendly Way

[Chris Mullins] wanted to automate opening and closing the slats of mini blinds in his apartment, and came up with a system to do it as a fun project. Manually opening and closing the slats means twisting a rod. Seems straightforward to automate that, but as usual when having to work around something that already exists, making no permanent alterations, complications arose.

The blinds are only 1 inch wide, leaving little room for mounting any sort of hardware. While there is a lot of prior art when it comes to automating blinds, nothing he found actually fit the situation [Chris] had, so he rolled his own.

The rod that is normally twisted to control the blinds is removed, and the shaft of a stepper motor takes its place. [Chris]’ mounting solution is made to fit blinds with narrow 1 inch tracks (existing projects he found relied on 2 inch tracks) and the 3D printed mount is fully adjustable, so the 28BYJ stepper motor can be moved into exactly the right position. Speaking of the stepper motor, the 28BYJ motor is unipolar but the A4988 driver he wanted to use is for bipolar steppers only. Luckily, cutting a trace on the motor’s PCB is all it takes to turn a unipolar motor into bipolar.

To drive the motor and provide wireless functionality, the whole thing works with a Wemos D1 ESP8266, an A4988 stepper driver, and a buck converter. While it worked fine as a one-off on a perfboard, [Chris] used the project as an opportunity to learn how to make a PCB using KiCad; the PCB project is here on GitHub and the ESP8266 runs the ESPHome firmware. Be sure to check out the project page on his blog for all the details; [Chris] links to all the resources there, and covers everything from a bill of materials to walking through configuration of ESPHome with integration into the open-source Home Assistant project.

Looking to control natural light but blinds aren’t your thing? Maybe consider automated curtains.

The Ever-Accelerating Automation Of Fast Food

In the fast food industry, speed is everything. The concept has never just been about cooking quickly. Players in this competitive space spend huge fortunes every year on optimizing every aspect of the experience, from ordering, to queueing, to cleaning up afterwards. And while fast food restaurants are major employers worldwide, there’s always been a firm eye cast over the gains that automation has to offer.

Flipping Burgers

In the West, fast food most commonly brings burgers to mind. Preparing a quality burger requires attention to the grade of meat, fat content, as well as the preparation steps before it hits the grill. Then it’s all about temperature and time, and getting just the right sear to bring out the natural flavors of the beef. While a boutique burger joint will employ a skilled worker to get things just right, that doesn’t fly for fast food. Every order needs to be preparable by whichever minimum-wage worker got the shift, and be as repeatable as possible across entire countries, or even the world, to meet customer expectations.

Flippy ROAR (Robot On A Rail) at work on the fryers in a White Castle in Chicago.

In their efforts to improve efficiency, White Castle have taken the bold step of installing a robotic burger flipper, imaginitively named Flippy. Built by Miso Robotics, the robot hangs from a ceiling rail to minimise the space taken up in the kitchen area. Based on a Fanuc robot arm, the system uses artificial intelligence to manage kitchen resources, Flippy is capable of managing both the grill and fryers together to ensure fries don’t get cold while the burgers are still cooking, for example. Currently undergoing a trial run in Chicago, White Castle has ambitions to roll the technology out to further stores if successful.

We’ve seen other robotic burger systems before, too. In late 2018, our own [Brian Benchoff] went down to check out Creator, which cooks and assembles its burgers entirely by machine. Despite suspicions about the business model, Creator have persisted until the present day with their unique blend of technology and culinary arts. Particularly impressive were their restaurant modifications in the face of COVID-19. The restaurant received an overhaul, with meals being robotically prepared directly in a take-out box with no human contact. Take-out meals are double-bagged and passed to customers through an airlock, with a positive-pressure system in the restaurant to protect staff from the outside world.

Pizzabots

Pizza is a staple food for many, with high demand and a stronger dependence on delivery than other fast food options. This has led to the industry exploring many avenues for automation, from preparation to order fulfillment.

In terms of outright throughput, Zume were a startup that led the charge. Their system involves multiple robots to knead dough, apply sauce and place the pie in the oven. Due to the variable nature sizes and shapes of various toppings, these are still applied by humans in the loop. Capable of turning out 120 pizzas per hour, a single facility could compete with many traditional human-staffed pizza shops. They also experimented with kitchens-on-wheels that use predictive algorithms to stock out trucks that cook pizzas on the way to the customer’s door. Unfortunately, despite a one-time $4 billion USD valuation, the startup hit a rocky patch and is now focusing on packaging instead.

Picnic aim to make lots of pizza, fast. Their business model involves working directly with existing restaurants, rather than creating their own fast-food brand from scratch.

Picnic have gone further, claiming an output rate of up to 300 twelve-inch pies an hour. The startup aims to work with a variety of existing pizza restaurants, rather than striking out as their own brand. One hurdle to overcome is the delivery of a prepared pizza into the oven. There are many varieties and kinds of pizza oven used in commercial settings, and different loading techniques are required for each. This remains an active area of development for the company. The company has a strong focus on the emerging ghost kitchen model, where restaurants are built solely to fulfill online delivery orders, with no dining area.

Domino’s is one of the largest pizza companies in the world, and thus far have focused their efforts on autonomous delivery. The DRU, or Domino’s Robotic Unit, was launched to much fanfare, promising to deliver pizzas by a small wheeled robotic unit. Equipped with sensors to avoid obstacles and GPS navigation, the project has not entered mainstream service just yet. However, between this and the multitude of companies exploring drone delivery, expect to see this become more of a thing in coming years.

Despite the marketing sizzle, the DOM Pizza Checker does not project holograms.

A more immediate innovation from Domino’s has been the DOM Pizza Checker. With customer complaints about pizza quality plaguing the chain, the pizza checker is an AI-powered visual system. It’s responsible for determining if the correct pizza has been made, with the right toppings and good distribution. An impressive practical use of AI imaging technology, it sounds an alarm if the pizza isn’t up to scratch, prompting it to be remade. However, it has come under scrutiny as a potential method to harass franchisees and workers. Additionally, the limitations of the system mean that Domino’s are still perfectly capable of turning out a bad pizza on occasion.

Other Efforts

One of the most visible examples of fast food automation is the widespread adoption of order kiosks by McDonalds, which kicked off in earnest in 2015. The majority of stores in the US now rely on these to speed up the ordering process, while also enabling more customization for customers with less fuss. Over-the-counter ordering is still possible at most locations, but there’s a heavy emphasis on using the new system.

McDonald’s automated beverage dispenser will be a familiar sight to many. Considered a great help when it works, and a great hindrance when it jams, spills, or simply shuts down.

In general, online ordering and delivery has become the norm, where ten years ago, the idea of getting McDonalds delivered was considered magical and arcane. This writer made seven attempts to take advantage of an early version of the service in China in 2015, succeeding only once, largely due to a lack of understanding of addresses written in non-Latin characters. However, due to the now-ubiquitous nature of services like Ubereats, Postmates, and Menulog, it’s simple for any restaurant to largely automate their ordering and fulfillment process, and reach customers at a distance from their brick-and-mortar locations.

Other efforts are smaller in scope, but contribute to great efficiency gains back-of-house. McDonalds and other chains have widely adopted automated beverage systems. Capable of automatically dispensing cups and the requisite fluids, they take instructions directly from the digital ordering system and take the manual labor out of drink preparation. They’re also great at slightly underfilling the cups, in a way that any human would consider incredibly rude.

Conclusion

Robots in the fast-food kitchen stand to reduce or eliminate tedious, repetitive work. Robots don’t get sick, and less human labour means fewer rostering hassles. It seems to be a foregone conclusion that more automation is on the way, and while some startups may falter, others will surely succeed. Your next meal may just yet be entirely prepared by a robot, even if it’s still delivered by a tired grad student on a moped. Come what may!

 

Automated Part Removal Gets Serious With The Chain Production Add-on

Giving a 3D printer the ability to remove its own prints means that it can crank out part after part automatically, without relying on a human operator between jobs. [Damien Weber] has done exactly that to his Prusa MK3/S printer, with what he calls the Chain Production Add-on.

[Damien]’s approach is one we haven’t quite seen before. When printing is complete, a fan cools the part then an arm (with what looks like utility knife blades attached at an angle) swings up and behind the bed. The arm zips forward and scoops the print off the bed, dumping the finished part in the process. It’s all made from 3D printed parts, aluminum extrusion and hardware, two stepper motors, and a driver PCB. The GitHub repository linked above holds all the design files, but there is also a project page on PrusaPrinters.org.

Not quite sure how it all works? Watch it in action in the video embedded below.

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Home Monitoring, Without All The Sensors

Smart homes come with a lot of perks, not least among which is the ability to monitor the goings-on in your home, track them, and make trends. Each piece of monitoring equipment, such as sensors or cameras, is another set of wires that needs to be run and another “thing” that needs to be maintained on your system. There are sometimes clever ways of avoiding sensors, though, while still retaining the usefulness of having them.

In this build, [squix] uses existing sensors for electricity metering that he already had in order to alert him when his oven is pre-heated. The sensor is a Shelly 3EM, and the way that it interfaces with his home automation is by realizing that his electric oven will stop delivering electricity to the heating elements once it has reached the desired temperature. He is able to monitor the sudden dramatic decrease in electricity demand at his house with the home controller, and use that decrease to alert him to the fact that his oven is ready without having to install something extra like a temperature sensor.

While this particular sensor may only be available in some parts of Europe, we presume the idea would hold out across many different sensors and even other devices. Even a small machine learning device should be able to tell what loads are coming on at what times, and then be programmed to perform functions based on that data.

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