Schlagwort: Nano 33 IoT

  • Tecnoseta revives the silk industry with open-source innovation

    Tecnoseta revives the silk industry with open-source innovation

    Reading Time: 3 minutes

    The silk industry has a rich history in Italy, but modern challenges have brought this centuries-old tradition to the brink of decline. Once a cornerstone of the rural economy in Italy, with a strong presence in Zagarolo, Rome, silk production has dwindled in the country due to industrial developments, synthetic fibers’ growing popularity, and fierce price competition from foreign exporters. Enter Tecnoseta, a small startup founded in 2019 with a bold mission: to rebuild and innovate the silk production chain, making it 100% Made in Italy.

    F:\WEB SITE\ECOMUSEO_SITO.IT\Foto\Baco2.jpgBaco2

    By combining traditional silk production expertise with modern Industry 4.0 technology, Tecnoseta’s founders have envisioned a sustainable, modular system to produce high-quality Italian silk. Their goals include not only manufacturing efficient, high-tech machinery but also revitalizing rural communities and offering hope to younger generations by creating local job opportunities. 

    F:\TECNOSETA SRL\FOTO\1. LINEA ALAMO Maceratore_Aspo_ Rereeling\20231027_102142 Baneasa.jpg20231027_102142 Baneasa

    “We’ve grown alongside Arduino. As the platform evolved, we were ready to seize the new possibilities.” – Maddalena Mariani, co-founder and CEO of Tecnoseta

    F:\TECNOSETA SRL\FOTO\PEXP1193_Moment.jpgPEXP1193_Moment

    Tecnoseta turned to Arduino’s accessible and reliable technology to bring their vision to life. Thanks to our open-source platform, their in-house team has developed a modular line of high-performance machinery tailored for each step of silk production, including reeling, re-reeling, twisting, and spooling.

    Using the Arduino Nano Every and Nano 33 IoT, they implemented automated processes and sensor-based monitoring across their specialized equipment. This allows for real-time fault detection, such as alerting operators when a silk thread breaks. This innovation drastically reduces downtime and improves efficiency, even for small-scale production.  

    F:\TECNOSETA SRL\FOTO\Claudio al torcitoio 2.jpgClaudio al torcitoio 2

    The modularity of Tecnoseta’s system means clients can scale operations according to their needs, from artisanal to industrial. The machines are also designed to integrate with renewable energy sources like solar panels, reflecting a strong commitment to sustainability.

    F:\TECNOSETA SRL\FOTO\PROFESSIONALI\Pollon_Aspo Maceratore Seta\DSC00284.jpgDSC00284

    Now the company is looking to the future, exploring ways to enhance their machinery with advanced sensors for predictive maintenance. 

    Leveraging tools like Arduino Cloud and the Opta micro PLC, Tecnoseta plans to collect data from the machines to monitor their performance and quickly intervene remotely in case of any issues, ensuring even greater reliability and precision. As their technology evolves, the company’s mission remains rooted in their heritage: combining cutting-edge innovation with traditional craftsmanship to create a sustainable future for the Italian silk industry.

    F:\TECNOSETA SRL\FOTO\Bachi da Seta prima e dopo imbozzolamento\bachi\20200616_201007.jpg20200616_201007

    Tecnoseta is now working within an agritech framework, to develop high-tech architectures and AI models for the automated management of silkworm breeding. “By supporting the transition of Italy’s sericulture to truly modern standards, we aim to have a positive impact on the local territory by attracting highly specialized professionals. What’s more, it will add to Italy’s competitive edge while making the supply chain more efficient and sustainable,” says Maddalena Mariani, co-founder and CEO. 

    The post Tecnoseta revives the silk industry with open-source innovation appeared first on Arduino Blog.

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  • This maker designed a custom flight controller for his supercapacitor-powered drone

    This maker designed a custom flight controller for his supercapacitor-powered drone

    Reading Time: 2 minutes

    Basic drones are very affordable these days—you can literally find some for less than the cost of a fast food drive-thru meal. But that doesn’t mean drones are easy to control. That is actually quite difficult, but manufacturers are able to work off of established reference designs. In a video that perfectly illustrates the difficulty, The Tinkering Techie attempted to make a supercapacitor-powered drone with his own custom flight controller. 

    Most airplane designs have inherent aerodynamic stability. Even without power, they can continue to glide. Even helicopters have some inherent stability in the form of autorotation. Quadrotor drones do not—they need constant power and very frequent motor control updates just to stay aloft. Even the slightest control error will result in catastrophic failure. Despite knowing the challenge, The Tinkering Techie wanted to try making his own flight controller.

    Aside from the custom flight controller, this drone is also unique for its power storage. Instead of conventional lithium batteries, it has a bank of supercapacitors. Those can fully charge in seconds—though they don’t store energy well over long periods of time. 

    The job of the flight controller is directing power from the supercapacitors to the motors (brushed DC motors, in this case) in a very precise manner. An Arduino Nano 33 IoT board oversees that process and The Tinkering Techie chose it because it has onboard sensors useful for a quadcopter, including a gyroscope and an accelerometer. A custom PCB hosts the Arduino and the supercapacitors, while a simple 3D-printed frame ties everything together.

    Unfortunately, this isn’t a success story and The Tinker Techie ultimately failed to achieve stable flight. The are many potential reasons for that, but one of the most glaring was the use of brushed DC motors, which can’t respond as fast as brushless DC motors can — an important factor for a drone.

    [youtube https://www.youtube.com/watch?v=s_Mqow2XjDA?feature=oembed&w=500&h=281]

    The post This maker designed a custom flight controller for his supercapacitor-powered drone appeared first on Arduino Blog.

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  • Get notified of impending floods with this Arduino Nano 33 IoT-based display

    Get notified of impending floods with this Arduino Nano 33 IoT-based display

    Reading Time: 2 minutes

    As climate change continues to worsen, events such as heavy rains, hurricanes, and atmospheric rivers have only intensified, and with them, large amounts of flooding that pose serious risks to life and property. Jude Pullen and Pete Milne, therefore, have responded by creating a “physical app” that can show the potential for flood dangers in real-time with sound, lights, and an ePaper display.

    The Arduino Nano 33 IoT powering the Flood Alert device sources its data from the UK Environmental Agency’s API to get statistics on an area’s latest risk level along with an extended description of what to expect. Initially, the electronics were mounted to a breadboard and housed within a cardboard enclosure, but a later revision moved everything to soldered protoboard, a 3D-printed case, and even added a piezoelectric buzzer to generate audible alerts.

    For now, the Flood Alert’s sole source of data is the aforementioned API, but Pullen hopes to expand his potential data sources to include “hyper-local” sensors that can all be aggregated and analyzed to give a much more precise view of flooding in a smaller area.

    [youtube https://www.youtube.com/watch?v=GEiZtaUzWaQ?start=6&feature=oembed&w=500&h=281]

    To learn more about Flood Alert and its myriad applications to local communities and beyond, check out Pullen and Milne’s well-detailed Instructables tutorial.

    The post Get notified of impending floods with this Arduino Nano 33 IoT-based display appeared first on Arduino Blog.

    Website: LINK

  • BrainPatch.AI: How a British neurotech startup built a working prototype fast, using Arduino Nano 33 IoT

    BrainPatch.AI: How a British neurotech startup built a working prototype fast, using Arduino Nano 33 IoT

    Reading Time: 3 minutes

    The field of neurotechnology has been advancing rapidly in recent years, opening up to safe and effective non-invasive interfaces that can deliver tiny milliamp currents to the right stimulation location on the head, neck or body. One example of the new players in this field is BrainPatch.AI, a Cambridge-based neurotech startup, which has developed an advanced brain stimulation headset that aims to give wearers a meditative and stress-free state of mind. 

    BrainPatch co-founder and CEO, Dr Nickolai Vysokov, explains: “Our innovative headphones are designed to gain indirect access to the vagus and the vestibular nerves via electrodes placed just behind the ears. The vagus nerve regulates the ‘rest and digest’ response of the nervous system, and stimulating it is known to lead to reduction of stress, improvement of heart rate variability, better communication between the mind and the body, and an improved overall state of wellbeing in general.”

    Prototyping at mind-bending speed

    Ordinarily, the time and effort required to produce a range of working prototypes would take larger companies years to accomplish, let alone a startup, which is why BrainPatch.AI chose to use a range of Arduino boards for their initial designs and testing. What began as a simple Arduino UNO-based circuit quickly evolved into an AI-enabled neuromodulator, leveraging the Arduino Nano 33 IoT’s built-in internet connectivity. Mobile devices are connected to the board via Bluetooth® Low Energy to allow precision protocol delivery and ability to adjust the protocol through Python® and integration with other devices. Altogether, the capability to leverage Arduino’s vast collection of libraries and hardware ecosystem ensured rapid progress could be made in a cost-effective manner.

    Finding like-minded partners is the key to success!

    As a leading startup in the emerging neurotechnology space, BrainPatch.AI  had the opportunity to meet with Arduino co-founder Massimo Banzi at Hardware Pioneers Max 2023 in London. The team was eager to demonstrate how effective their neuro stimulation device is, and to share how integrating Arduino hardware enabled them to move quickly – and can also be the go-to solution for many other startups and neurotechnology enthusiasts in the future. Nickolai adds, “Arduino is simply the best solution for any hardware / middleware / software startup prototyping, and we were blessed to have Arduino products and third-party libraries available when we needed them the most, to kickstart the process of transformation from ideas onto the physical objects. And now, we are ready to share our technology and our libraries with the world and other startups. If you are a co-founder of a startup, you must try our device when you get overstretched and overstressed. It’s life changing – and all thanks to Arduino.” 

    The current iteration of the company’s e-Meditation and VR enhancement products along with more information about the science behind non-invasive neuromodulation can be found here on BrainPatch’s website.

    The post BrainPatch.AI: How a British neurotech startup built a working prototype fast, using Arduino Nano 33 IoT appeared first on Arduino Blog.

    Website: LINK

  • The new Auxivo EduExo Pro helps students with exoskeleton research

    The new Auxivo EduExo Pro helps students with exoskeleton research

    Reading Time: 2 minutes

    Emerging technologies initially develop at a slow pace and that is due in large part to the lack of resources available to students. Complex technology is built on existing knowledge and higher education students need the tools to gain hands-on experience. To help educate the next generation of exoskeleton engineers, Auxivo has just introduced the newly updated EduExo Pro exoskeleton kit.

    The Auxivo EduExo Pro is an educational exoskeleton platform designed to help students learn fundamentals via a project-based learning approach, with enough flexibility for those students to experiment with their own designs. It originally launched on Kickstarter in 2021 and now Auxivo has released an updated version.

    The hardware in the kit consists of structural parts, mechanical components, motorized actuators, sensors, and control electronics. The kit includes everything necessary — except 3D-printed parts — to build a full-arm exoskeleton that has a 2DOF (degrees of freedom) shoulder joint and a 1DOF elbow joint.

    For maximum compatibility and versatility, the Auxivo EduExo Pro operates under the control of an Arduino Nano 33 IoT board. Students can take advantage of the powerful Arduino IDE to program sophisticated behaviors and integrate that with other software, such as Unity 3D. 

    The provided handbook will walk students through assembling and programming the arm exoskeleton, but educators can also create their own curriculums or let students devise new designs. That makes the Auxivo EduExo Pro perfect for high school and university-level engineering courses. 

    The Auxivo EduExo Pro is available on the Auxivo shop right now for CHF1,790.00 (about €1,890 / $2,000 USD). 

    The post The new Auxivo EduExo Pro helps students with exoskeleton research appeared first on Arduino Blog.

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  • Easily add Python-controlled GPIO pins to any computer

    Easily add Python-controlled GPIO pins to any computer

    Reading Time: 2 minutes

    Let’s say that, hypothetically, you wanted to use your computer to blink an LED or read the state of a button. Could you? Almost certainly not — at least not without additional hardware. Most modern computers don’t provide any interface for direct interaction with low-level components. That’s why Nick Bild developed a device called USBgpio that lets users easily add Python-controlled GPIO pins to any computer.

    USBgpio connects to any modern PC via USB. It has a row of exposed GPIO pins and users can control their states programmatically using Python. If you noticed that this sounds a lot like connecting an Arduino board to a computer, then you’re most of the way to understanding the concept. That’s because the enclosure does, indeed, contain a Nano 33 IoT. The header pins on the top of the USBgpio device connect directly to their counterparts on the Arduino.

    This provides utility (beyond the Arduino alone) because of the sketch that accepts serial commands sent by Python code. By using the USBgpio library, a user can set the state of any of the GPIO pins with a simple command. Of course, it is also possible to read the value of a pin.

    Instead of flashing a new sketch to the Arduino every time they want to do something, a user can run a Python script directly on their computer. Or they can send commands in real-time using a Python interpreter. This provides an interesting interaction style that may appeal more to some users than traditional workflows.

    [youtube https://www.youtube.com/watch?v=I5nCYR48eAI?feature=oembed&w=500&h=281]

    The post Easily add Python-controlled GPIO pins to any computer appeared first on Arduino Blog.

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  • Off-grid remote generator starter helps avoid trekking outside in bad weather

    Off-grid remote generator starter helps avoid trekking outside in bad weather

    Reading Time: 2 minutes

    Living off the grid is a dream for many people, but it also presents unique challenges that are otherwise absent in our urban-centric lifestyles. One of the largest adjustments one has to make is the lack of readily available power, as it typically comes from renewable wind/solar or generator setups. In element14 Presents host Kaleb Clark’s case, his Honda EU-7000iS generator works in combination with some solar panels around his property, although the generator is located nearly 200 feet away and downhill, making it a very tough journey to operate in bad weather.

    After finding a bypass cable with one pair of leads for enabling the generator and another pair for powering on the starter motor, Clark got a couple relays that could bridge their contacts together programmatically. In order to communicate the current output of the generator, solar panels, battery, and if the motor should run, a pair of Arduino Nano 33 IoT boards were chosen for both the house and generator sides of the project. They send data through Wi-Fi and MQTT to stay in consistent synchronization while either one is also connected to a few seven-segment display modules and MAX7221 LED drivers for showing the most recent data.

    While inside the house, Clark is able to simply hold down a button and watch how the generator across his property roars to life and begins producing measurable power output to the display. More information about this project can be seen in Clark’s video below!

    [youtube https://www.youtube.com/watch?v=0L8hSVrNQQo?feature=oembed&w=500&h=281]

    The post Off-grid remote generator starter helps avoid trekking outside in bad weather appeared first on Arduino Blog.

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  • A DIY autonomous lane keeping system on a budget

    A DIY autonomous lane keeping system on a budget

    Reading Time: 2 minutes

    Despite overconfident proclamations from high-profile players in the tech and automotive industries, we’re still a long way from fully autonomous self-driving cars. Current prototypes work well under ideal conditions, but are easily thwarted by everyday real world anomalies. Lane keeping, however, is a much more approachable challenge and Computerphile was able add such functionality to an older vehicle.

    Many of today’s cars have lane keeping capability and that usually works by looking at the lane lines on the road. Because drive-by-wire is now the norm, the vehicle can steer itself to remain within the lines. That works well on interstates and highways, because it only needs to perform small adjustments without any turns. This DIY lane keeping system works in a slightly different way. It looks at the entire scene in front of the car and uses an AI to determine if it should adjust the steering.

    Before continuing, it is worth noting that Computerphile wanted to emphasis that this is not safe for use in the real world. There are too many potential safety issues and it would require extensive testing before it would be responsible to even try it on a public road.

    With that in mind, this system’s performance was only simulated. It uses a trained convolutional neural network (CNN) to indicate how the car would steer itself if it had actual control over the steering. Computerphile trained that CNN using a laptop, a webcam, and an Arduino Nano 33 IoT. The computer records video frames while also recording the orientation of the Arduino through its built-in six-axis IMU. With the board attached to the steering wheel, that orientation corresponds to the angle of the steering wheel.

    Through the magic of machine learning, the CNN was able to associate types of imagery with steering angles. So it might see a bend in the road and know that that means the steering wheel needs to turn.

    [youtube https://www.youtube.com/watch?v=5G56i_he79M?feature=oembed&w=500&h=281]

    As Computerphile shows, this works fairly well. But it is also easily confused. It would take a lot more training data in a larger variety of conditions to produce a reliable system. In theory, however, such a system would be more robust than standard lane keeping systems that look at road lines.

    The post A DIY autonomous lane keeping system on a budget appeared first on Arduino Blog.

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  • This internet uptime indicator reduces frustration

    This internet uptime indicator reduces frustration

    Reading Time: 2 minutes

    Bandwidth may have increased dramatically over the past couple of decades, but internet connections are often still quite unreliable. For people with unreliable connections, it becomes a chore to check a browser over and over again to find out when the internet is back up. To avoid that hassle, Emily Velasco built this monitor.

    This device has only one purpose: to indicate when its internet connection is functioning or not. All it does is ping Google.com and checks if it gets a response. If it does, the device lights up in green to show everyone in the vicinity that the internet is working. If it doesn’t, it lights up in red.

    Velasco has a very distinct design aesthetic, which is readily apparent here. The unit’s indicator LEDs reside in a small animal skull’s eye sockets for some “oddities and curiosities” style. That skull sits under a dome of glass, which is a repurposed security camera housing. Velasco has many animal skulls around her home, so this device blends right in.

    Inside that base there is an Arduino Nano 33 IoT board, though any WiFi-enabled model should work for this purpose. The sketch is very simple, as it only needs to ping Google.com and then control the two LEDs.

    https://platform.twitter.com/widgets.js

    While the macabre appearance may not appeal to everyone, the functionality is something that many people will appreciate.

    The post This internet uptime indicator reduces frustration appeared first on Arduino Blog.

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  • Lumos finally enables wearable spectroscopy research

    Lumos finally enables wearable spectroscopy research

    Reading Time: 2 minutes

    Spectroscopy is a field of study that utilizes the measurement of electromagnetic radiation (often visible light) as it reflects off of or passes through a substance. It can, for instance, help researchers determine the composition of a material, as that composition influences how the material reflects light. Spectroscopy is also used in medicine, but traditionally requires that patients visit a lab. To enable long-term spectroscopic analysis, a team of engineers built a wearable spectroscopy sensor called Lumos.

    Lumos comes in two forms: a smartwatch-like wearable wristband and a fingertip model that resembles the pulse oximeters that nurses put on your finger when you go in for a checkup. The latter is meant for use in doctor’s offices and labs, but the former was designed for patients to wear as they go about their daily lives. It would continue to collect spectroscopic data as they do, which could provide valuable insight. Such long-term data collection would help physicians observe how conditions progress or to see conditions that don’t present consistently.

    The engineers chose an A7341 spectral sensor for Lumos because it is compact, but still has a large sensing range. An Arduino Nano 33 IoT development board provides power to the A7341, receives the data from the A7341 through an I2C connection, and then sends the data to a base station via WiFi. Power comes from a 400mAh lithium-ion battery, which lasts for around five hours before it needs recharging. That’s five hours of spectroscopic data to analyze — far more than can be gathered using traditional in-lab instruments.

    Image credit: Watson and Kendel et al.

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  • Arduino brings birthday cake to life

    Arduino brings birthday cake to life

    Reading Time: 2 minutes

    A good birthday cake is all about the decoration. Usually that comes in the form of fancy frosting, fondant flourishes, and crazy candles. But what if you got electronics involved? That’s the question Natasha Dzurny answered when she used an Arduino to bring a birthday cake to life with epic LED lighting.

    WS2812B individually addressable RGB LEDs, commonly referred to by Adafruit’s “NeoPixel” trade name, are unique because a user can control the color and brightness of every LED in a chain through a single data wire. Each LED passes the data along to the next, with control commands going to the addressed LED. The user can control as many LEDs as they want using only a single digital I/O pin on a microcontroller.

    In this case, Dzurny used two Adafruit 8×32 flexible NeoPixel matrices and a NeoPixel strip. The matrices display animations and messages, while the NeoPixel strip sits atop the cake to accent a small disco ball. An Arduino Nano 33 IoT board controls all of those LEDs using the Adafruit GFX library. But while hundreds of LEDs can share a single data line, power distribution is more complicated and Dzurny had to break out power injection points.

    The cool thing about using NeoPixel matrices for a cake is that Dzurny was able to cover them in a thin layer of white fondant, which acts as a natural diffuser that blends right into the design. The messages are clearly visible, but party-goers wouldn’t even notice the LEDs underneath the fondant when they’re turned off.

    The post Arduino brings birthday cake to life appeared first on Arduino Blog.

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  • Monitoring environmental pollution with the Arduino MKR WAN 1300

    Monitoring environmental pollution with the Arduino MKR WAN 1300

    Reading Time: 2 minutes

    The scourge of air pollution claims several million lives globally each year, with industrial processes and energy production accounting for much of it. Because of its harmful nature, governments often set up air quality monitoring stations, although they have to cover large areas and yield low resolution data. To monitor the air quality of a neighboring ecological reserve, Guillermo Perez Guillen created a small, portable toolkit that can record data from almost anywhere and send it to the cloud.

    Guillen’s system relies on two Arduino MKR WAN 1300 boards, which communicate with each other over the LoRaWAN long-range network, along with a Nano 33 IoT for sending the received data to a web API endpoint over WiFi. The transmitting MKR WAN 1300 is connected to a suite of sensors that measure temperature, humidity, carbon dioxide, carbon monoxide, and volatile organic compounds (VOCs) in the air. Then, at preset intervals, each sensor is read and the resulting measurements are sent to an awaiting receiver MKR WAN 1300 board.

    Once the data packets have arrived, they are decoded and displayed on an attached 20×4 character LCD, as well as being sent over UART to a Nano 33 IoT. From here, values are written to a Thingspeak channel so they can be tracked over time. More information about this project can be found on Instructables.

    The post Monitoring environmental pollution with the Arduino MKR WAN 1300 appeared first on Arduino Blog.

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  • Robo-fish filters microplastics like a whale with krill

    Robo-fish filters microplastics like a whale with krill

    Reading Time: 3 minutes

    The world’s collective waste plastics don’t always stay in landfills. They often break down into microplastics that fill our oceans, then end up in our air, water supply, and food. According to an Orb Media study, 83% of the tested water samples from metropolitan areas all over the globe contained plastic fibers. One way to reduce microplastics before they end up in our bodies is to collect them where they float in lakes and oceans. For the Natural Robotics Contest, student Eleanor Mackintosh designed this robo-fish that filters microplastics like a whale eating krill.

    Mackintosh created the robo-fish concept and then the Natural Robotics Contest team turned it into a real robot. This robot, called “Gillbert” (we see you, Eleanor) is now an open source project and anyone can build it for themselves using the 3D-printable files published on GrabCAD. Gillbert contains mesh filters that collect plastic particles as water flows through its mouth and out of its gills. It swims through the water like a real fish by swinging its tail for propulsion and using its fins to steer.

    An Arduino Nano 33 IoT board controls Gillbert’s motors and monitors the sensors, which include a LSM6DS3 IMU (inertial measurement unit), a turbidity sensor, and a light/color sensor. The Arduino receives commands through WiFi via a tethered receiver that floats on the surface. The operator pilots Gillbert using a Microsoft Xbox One controller and power comes from a 5000mAh USB battery bank. 

    The Natural Robotics Contest team tested Gillbert in a lake in Guildford, England with good results. While the robo-fish lacks the instruments to analyze microplastics, it can collect them and bring them back to researchers for study. On its own, Gillbert (or even a fleet of Gillberts) can’t collect enough microplastic to make a real-world difference. But the research that it enables could be very beneficial.

    Boards:Nano 33 IoT
    Categories:Arduino

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  • The Airio Explorer 1 is a Nano 33 IoT-based indoor gas monitor

    The Airio Explorer 1 is a Nano 33 IoT-based indoor gas monitor

    Reading Time: 2 minutes

    The environments we reside in can have massive effects on our health, as poor air quality, crowded spaces, or uncomfortable temperatures can all lead to certain illnesses. Of these metrics, Tindie seller AppliedSBC has focused on air quality since too much CO2 or too little oxygen quickly impact health with sometimes grave consequences.

    AppliedSBC’s Airio gas monitoring platform, with the Airio Explorer 1 being the first product in the series, utilizes a Nano 33 IoT board to control several different sensors. The primary one is a gas sensor, which can measure concentrations of carbon dioxide and oxygen gases with relative accuracy. In addition to these datapoints, there is a secondary temperature and relative humidity sensing module that can provide even more information about the surrounding air. The kit supports continuous monitoring, which logs data to either a microSD card (up to four years of data) or to a live web portal once every second.

    With these sensors, an LED indicator, and a programmable alarm for alerting users to hazardous air quality, the Airio Explorer 1 is a fast way to deploy a portable gas monitoring device. AppliedSBC recommends using it at home, in greenhouses, or even in laboratories where maintaining certain environmental conditions can be important. 

    Boards:Nano 33 IoT
    Categories:Arduino

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  • The UV Budgie shows IoT alerts in a fun way

    The UV Budgie shows IoT alerts in a fun way

    Reading Time: 2 minutes

    Arduino Team — September 14th, 2022

    The Internet of Things (IoT) is now well-established and households around the world contain many IoT devices. Most of them were designed to blend as seamlessly as possible into their owners’ lives, which means that they tend to be unobtrusive. But “unobtrusive” is the last adjective you want to describe an important notification, which is why Jude Pullen built the UV Budgie.

    For those of you without an interest in ornithology, “budgie” is a shortening of “budgerigar” and is a nickname for the common parakeet. That name is appropriate for this device as it features an automata budgie that flaps and squawks according to the peak UV level for the day. UV rays can be dangerous, so this flapping budgie is a great way to get your kids attention and remind them to pack some sunscreen. A ding or announcement from Alexa won’t tear their eyes away from Minecraft, but a fluttering avian might.

    An Arduino Nano 33 IoT board pulls the UV index from the Met Office Datapoint Service API in the UK. It then displays that data on a 2.9” Waveshare ePaper screen. If the UV index for the day is at dangerous levels, then the Arduino will use an Adafruit Servo Driver board to turn a servo that drives the automata budgie mechanism. At the same time, it will play a sound file through an Adafruit Audio FX Sound Board. The device’s enclosure and the budgie automata mechanism are all 3D-printable, so you can build The UV Budgie for yourself. But if you live outside of the UK, you’ll need to utilize another service to pull the UV index. 

    [youtube https://www.youtube.com/watch?v=ewFgSpgAaW0?feature=oembed&w=500&h=281]

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  • Make your own motorcycle monitor for the race track with a Nano 33 IoT

    Make your own motorcycle monitor for the race track with a Nano 33 IoT

    Reading Time: 2 minutes

    Arduino Team — August 17th, 2022

    If you’ve ever had the pleasure of riding a motorcycle on a track, then you know that it quickly becomes competitive — even if the competition is yourself. You want to cut your lap times, increase your lean angle, brake later after a straight, and accelerate harder as you come out of a turn. But the only way to get objective data on your improvement is to monitor your real performance. This device designed by Jesus Soriano collects that data so that you can track your progress from one track day to the next.

    There are commercial products on the market that provide similar functionality, but they’re expensive and give you little control over operation. This project utilizes open hardware, so you can hack it to your heart’s content and save some money that is better spent on tires. The important components include: an Arduino Nano 33 IoT board, a TinyCircuits GPS shield, a SparkFun Power Supply Stick, a Bitcraze Micro SD Card Deck, and a 1000mAh lithium-ion battery. Soriano simply stuffed those components in his motorcycle’s tail storage area under the seat, but you could always 3D-print a dedicated enclosure if your bike doesn’t have tail storage.

    The data collected comes from both the Arduino’s built-in sensors and the GPS location. Those let it monitor lean angle, forward/backward tilt, yaw (though that isn’t particularly useful for a motorcycle), acceleration, lap times, and even ambient temperature. By connecting to the internet through a smartphone hotspot, the device can upload sensor data to the Arduino IoT Cloud. With that service, you can view the data in beautiful graphs and on a map. Because the sensor data is timestamped, you can do things like look at the acceleration values after a turn or the lean angle in a turn. 

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  • Get connected to your Nano with the Screw Terminal Adapter

    Get connected to your Nano with the Screw Terminal Adapter

    Reading Time: 3 minutes
    Arduino Nano Screw Terminal Adapter

    The brand new Nano Screw Terminal Adapter turns up the speed on your prototyping efforts by giving you a fast, reliable way to hook up your boards. This awesome add-on is exactly what seasoned makers have been crying out for, and is now available from the Arduino Store.

    Let’s take a look at this mini mechanical marvel.

    A solderless solution

    With a finished project, you’re likely to make permanent connections to your Nano by soldering it. Even if you’re connecting it using a header strip, the wires, components, sensors and accessories will be soldered, crimped or attached in a permanent way to the controller side of your project. It makes perfect sense to do this, when you’re looking for a reliable connection.

    The trouble with permanent connections like this is that they’re… well, permanent! Soldering and de-soldering during the design and prototyping stage can become a real chore. And it’s not good for the components or the board itself, either.

    The Screw Terminal Adapter is what you need. It’s something we’ve been asked for a lot, giving people a way to make robust, fast, easy connections that can be changed just as easily.

    Easy access to all I/Os

    The Nano Screw Terminal Adapter features a double row of headers. The Nano drops into the two inner rows, giving you a second, outer set that lets you connecting using jumpers, wires or what have you.

    Then you have a third row of connectors on either side of the adapter with a screw terminal for each pin. The perfect way to connect wires or components in a reliable, but easily changeable way. It’s never been easier to develop and design a project that with these connection options.

    There’s even a 9×8 prototyping area with through plated holes for adding extra components, connections or accessories.

    Of course, this doesn’t have to only be for prototyping. The screw terminal is a long-established, trusted connection option, so there’s no reason it can’t become a permanent fixture in your project. That’s totally up to you, and is quintessentially what this board is all about; giving you lots of reliable options.

    Get connected

    We can really see this becoming an essential part of any Ardunino lover’s or maker’s tool kit. That’s why they come in packs of three. Once you’ve used one, you’ll realize how vital they are. Being able to assemble, test, change and reassemble a project with the adapter is a time saving, labor saving gift.

    You can also pick them up bundled with your favorite Nano board, in which case you get one adapter and one board. A perfect prototyping partnership.

    The Nano Screw Terminal Adapter is now available in stock to purchase on the Arduino Store and will be available from our global network of reseller partners in the forthcoming days.

    Check it out, and tell us what you think!

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    Website: LINK

  • Designing a DIY watch with a brass ‘cyberpunk-y’ aesthetic

    Designing a DIY watch with a brass ‘cyberpunk-y’ aesthetic

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    Designing a DIY watch with a brass ‘cyberpunk-y’ aesthetic

    Arduino Team — June 20th, 2022

    The cyberpunk aesthetic, like several other genres, often takes the form of heavy and metallic body modifications or devices that are meant to signify a more futuristic society. Inspired by the video game Deus Ex, Redditor Star_11 had the idea to create their own smartwatch primarily out of soldered brass sheets and 3D-printed plastic.

    Within this space-age bracelet is an Arduino Nano Every, which controls the connected Crystalfontz SSD1320 flexible OLED display. On it, the watch can currently show the time and date, although other information such as the level of the 280mAh battery, alarms, and timers might be added in the future. Star_11’s plan is to also take a Nano 33 IoT and replace the Nano Every for extra IoT functionality or connect to a phone via Bluetooth®.

    Although the watch’s three-pin magnetic pogo connector appears to be used for recharging the device, Star_11 intended it for use with a custom input ring that slips around the wearer’s finger and houses a single pushbutton. However, later iterations might swap this out for a small joystick so that the GUI is easier to navigate.

    To see more about how Star_11 built this cyberpunk-themed smartwatch, head over to their Reddit post here.

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    Website: LINK

  • Remote indoor air quality monitoring with the Arduino Nicla Sense ME and Nano 33 IoT

    Remote indoor air quality monitoring with the Arduino Nicla Sense ME and Nano 33 IoT

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    Arduino Team — May 26th, 2022

    Most air quality-sensing devices integrate their sensors into the same enclosure as the display, which can make getting an accurate reading tough since the viewer is directly next to the unit and could potentially skew the values. This is why one element14 community member Enrique Albertos created his own portable air quality monitor that separates the sensing module from the screen.

    His system uses one Nicla Sense ME to gather air quality information about the surrounding environment with its onboard BME688 gas sensor. It is highly capable too, as it can quantify pressure, humidity, temperature, VOCs, VSCs, and various other harmful gases such as carbon monoxide. From here, the Nicla Sense ME sends its data over Bluetooth to an awaiting Nano 33 IoT board. The Nano is connected to a 1.8” TFT screen, which shows several pages of information that are cycled through by pressing one of the buttons at the bottom of the device.

    The first layout consists of a large gauge for the indoor air quality value, and just above it is the current time from an NTP server and the battery level. Underneath is the current temperature and the relative humidity. For a more historical view, Albertos designed a layout that contains several charts that plot values over time.

    You can read more about this project here in Albertos’ element14 blog post and see a demonstration in the video below.

    [youtube https://www.youtube.com/watch?v=d_gaja_FgpQ?feature=oembed&w=500&h=281]

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    Website: LINK

  • Introvention is a wearable device that can help diagnose movement disorders early

    Introvention is a wearable device that can help diagnose movement disorders early

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    Arduino Team — May 17th, 2022

    Conditions such as Parkinson’s disease and essential tremors often present themselves as uncontrollable movements or spasms, especially near the hands. By recognizing when these troubling symptoms appear, earlier treatments can be provided and improve the prognosis for the patient compared to later detection. Nick Bild had the idea to create a small wearable band called “Introvention” that could sense when smaller tremors occur in hopes of catching them sooner.

    An Arduino Nano 33 IoT was used to both capture the data and send it to a web server since it contains an onboard accelerometer and has WiFi support. At first, Bild collected many samples of typical activities using the Edge Impulse Studio and fed them into a K-means clustering algorithm which detects when a movement is outside of the “normal” range. Once deployed to the Arduino, the edge machine learning model can run entirely on the board without the need for an external service.

    If anomalous movements are detected by the model, a web request gets sent to a custom web API running on the Flask framework where it’s then stored in a database. A dashboard shows a chart that plots the number of events over time for easily seeing trends.

    To read more about Bild’s project, check out its write-up here on Hackster.io.

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    Website: LINK

  • Golf Ace helps you learn how to putt like the pros using tinyML

    Golf Ace helps you learn how to putt like the pros using tinyML

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    Arduino Team — May 9th, 2022

    Fancy golfing simulators are excellent for learning the best techniques such as balance and how to hold a club properly. However, their large cost puts them out of the reach of most people, so Nick Bild decided to create a far cheaper alternative that can still be beneficial. His Golf Ace system relies on a specially modified putter that runs a machine learning algorithm to give feedback about the quality of the putt.

    When the player is ready to begin using the club, they can press a button, after which the onboard accelerometer of a Nano 33 IoT begins recording the movements of the putter. He trained a K-means clustering anomaly detection algorithm with data from many correct motions in the Edge Impulse Studio, meaning that anything outside of the normal range can be recognized as a poor putt. From here, the model outputs if the recorded motion is close enough to correct, and if so lights up an RGB LED in green. Otherwise, the light turns red to signal poor technique. 

    In the future, Bild hopes to collect more data from proficient golfers in order to further refine his model and preload it into a club so that others can practice with high-quality putting data. Until then, you can read more about the project in his Hackster write-up.  

    [youtube https://www.youtube.com/watch?v=0Lobf9xCVeI?feature=oembed&w=500&h=281]

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    Website: LINK

  • This Nano 33 IoT-controlled bicopter uses a pair of rotors to achieve stable flight

    This Nano 33 IoT-controlled bicopter uses a pair of rotors to achieve stable flight

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    Arduino Team — February 14th, 2022

    The classic helicopter design that everyone is familiar with features a large central rotor that produces lift and a much smaller one towards the back, which prevents the helicopter from spiraling out of control. However, Redditor CCCanyon decided to take inspiration from Boeing’s CH-47 Chinook that leverages a pair of equally sized and offset rotors that work together to both move the helicopter while remaining steady.

    The most apparent feature of the project is the unique 3D-printed frame that houses the electronics, batteries, and motors required for flight. The controller is a single Arduino Nano 33 IoT, which constantly takes measurements from its onboard LSM6DS3 six-axis IMU and sends that data through a PID algorithm to create small adjustments. The pilot is able to control the aircraft by manipulating a single-stick controller that sends commands from its LoRa SX1276 transceiver to the bicopter’s. Finally, the two rotors are spun by brushless DC motors that were set atop servo motors, which tilt them in order to modify the heading. 

    This project, along with the from-scratch code required to make it work, is very impressive, as can be seen in the demo video below. CCCanyon is also currently working on a second version of the bicopter, and it will be exciting to see which improvements have been made.

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    Website: LINK