Abstract Figure 1: The SmartWristband device being worn Monitor patients sent to self-isolate with the coronavirus by collecting their temperature and heart rate through a comfortable wristband and sending this data to the hospital through an interactive dashboard and ensure that they respect the isolation by alerting appropriate authorities if the user leaves their home. I decided to create a solution that would help care for people which have contracted a weak form of the virus. This is a category of patients which is often overlooked as their symptoms are not serious to warrant very close surveillance. However, this does not mean that their condition isn’t volatile. Due to this fact, I believe that monitoring the health of these patients is a priority. As it turns out, countries have different approaches for tending to these patients: some will hospitalise them (crowding hospitals with patients that could be monitored off-campus), while others send them to self-isolate at home. But there is a problem with the second option: a patient’s condition can quickly deteriorate. As a result, all patients must be monitored. Sure, there exists heavy, bulky equipment that does this. But the problems are obvious; as the majority of the sick population will exert weak forms of the virus, these expensive, uncomfortable devices do not have the capacity to scale and be deployed to the entire population. There are also situations in which patients who exhibit symptoms may grow restless and wish to leave their home, putting themselves and others at risk. So that this does not occur, the condition and status of patients should be monitored. Figure 2: The SmartWristband device being worn SmartWristband is a wristband held device that monitors the patient’s vitals and geolocation, caring for their safety while they fight the virus within the constraints of their home. The device is powered by an Arduino MKR GSM 1400 and is equipped with both an IR temperature and heart rate sensor collecting crucial information about the patient’s health. Elevated temperature and irregular heart rate are signs of the progression of the virus. The patient will not notice these changes immediately, SmartWristband aims to do this and stream the data live and securely to the hospital monitoring the patient. The device will also track the user’s location ensuring that they are at home at all times. All of this data is centralised in a scalable database allowing for thousands of these devices to be deployed internationally. Figure 3: The dashboard detailing the heart rate, temperature, location and other parameters for a specific patient The hospital will have access to a dashboard where they will be able to see the health of all the patients being monitored at a glimpse as well as a specific report going into the detailed state of each patient. Machine learning algorithms are also implemented in the application to predict the temperature and heart rate of the patient in the near future so that the hospital knows what to expect and when to hospitalise the patient. The patient also has access to a mobile dashboard showing them their heart rate and temperature as well as when they will need to charge their wristband. Figure 4: The mobile dashboard available to the patient displaying data collected by the device The device is comfortable enough for the patient to wear day and night without noticing it. SmartWristband will also notice if the user took the device off, alerting the hospital in this case. SmartWristband is a low-cost, scalable, open source solution for caring for patients sent to self-isolate with weak forms of the virus monitoring the development of their condition and alerting medical staff through machine learning and a simple-to-use dashboard experience if a patient requires attention. This way, hospitals can send patients home and monitor them without the need to allocate a lot of human resources. SmartWristband can ensure that these patients are contained at home and are taken care of, helping the world in the fight with the virus. Project Sumup This section will look at the functionality of the application and give a high-level understanding of what it is doing. Data CollectedData is collected by the device at intervals of 5 minutes. This is done to provide a real-time view of the condition of the patient while using the lowest possible battery consumption. The device collects two types of data: vital and location. Vital data refers to the heart rate and temperature of the patient while the location data refers to their geolocation. Application Frontend Figure 8: The frontend architecture diagramThe diagram above shows the architecture of the application running on the device. These are the steps taken by the device every 5 minutes. The device collects all the data, checks if it is worn by the user and then packages them and sends them to the backend through GSM. The device also keeps track of the time, it gets the time from a designated server and syncs its onboard RTC to this timestamp when it wakes up for the first time or after it is turned off. Application Backend Figure 9: The backend architecture diagramThe data sent by the device is received in the Azure IoT Hub. A stream analytics job extracts this data from the hub at short intervals of time and pushes it into a Cosmos DB database. The patient and doctor Power Bi reports then query this data at intervals of time from the database, run machine learning algorithms built into Power Bi and then display the data. The doctor’s dashboard then collects all patients monitored and provides a brief of their health. Why is this data collected? An analysis of the patient’s temperature and heart rate readings can indicate whether their current state is degenerating. Studies show that an irregular heart rate and high temperature are signs of the presence of the virus. If these vital signs degenerate over time (i.e. the temperature rises gradually) this is a sign that the condition of the patient may be worsening. The patient may not realise this until later, but the device will pick these signs up as they appear. The geolocation data is also collected by the device, this is done to ensure that the patient is staying at home in quarantine and is abiding by the rules of the isolation. Azure checks if the user is at home and will report this on the doctor dashboard. A look at the device I created the prototype with comfort in mind. The device is easily placed on the wrist of the patient, either on the left or right hand. It is equipped with a heart rate sensor and IR temperature sensor that stick out at the bottom of the device to touch the skin of the patient. These sensors provide precise measurements without causing discomfort. Note that for further temperature precision, the sensor should be placed in a location such as the under the arm in a pad. The device will use the raw data outputted by the heart rate sensor to check if it is being worn by the patient. The sensor will output a very specific pattern of data when it is in contact with skin and hence the lack of this pattern represents the device not being worn. Battery Life Figure 5: The patient dashboard highlighting the battery level of the device and the number of hours of battery leftRigorous testing was conducted to precisely measure the battery life of the device. The device has a total battery life of 8 days with a single charge. This means that if the patient is to be surveyed for two weeks, the battery would have to be recharged once. The battery can be charged while the device is being worn. Alternatively, data could be collected at intervals of 10 minutes, essentially doubling the device’s battery life as it would be sleeping between reads, consuming very little battery. The remaining battery life as well as the number of hours of battery life left is displayed on the patient and doctor dashboards. Cost of Development The cost of development in the case of the project consists of once-off and recurring costs. The cost of development for one device would be €70 including the enclosure. Recurring costs occur in the backend. I am using Hologram as my service provider costing me €5 to send data for 2 weeks per device. The backend costs including data streaming and the database are at €30 for 2 weeks. The total cost for 100 devices is approximately €7,035. Note that these devices are reusable. Note that the backend costs are scalable and will be the same regardless of the number of devices deployed. Costs can be dramatically reduced when buying components in bulk and using custom circuits. The Doctor Dashboard It is very important for the hospital to be able to monitor the health of these patients sent at home at all times and get alerts if they are not ok. The hospital has access to a dashboard showing the vitals of all patients monitored as well as a specific report for all of them. This allows doctors to be notified if a patient needs assistance and then can look at the patient in more detail to see exactly what the problem is. The doctor will receive a notification in the form of an email and alert in the dashboard if a patient is not at home, not wearing the device or has irregular temperature and/or heart rate. Figure 6: Tiles on the doctor dashboard highlighting core data from all patients being monitoredThe doctors will also get alerts through emails when a patient’s vitals are abnormal allowing action to be taken immediately. The report seen in the dashboard is split into 3 sections: the patient (giving details about the vitals), the location (location of the patient and if at home) and the device (battery level, ID). Machine learning is also used to predict the health of the patient in the near future showing the doctor if the patient’s health is getting worse over time. Patient Dashboard I think that patients should also be able to access this data to know how they are doing and become self-aware. Both a desktop and mobile experience is available for the patient so they can get their data on the fly. Note that forecasting and geolocation data is not displayed on the patient’s dashboard because they would not need that information. Figure 7: The dashboard the patient has access to on a desktop showing the data collected from the deviceMass Production and Scalability The device is suitable for mass production and scalable because of its small price point and ease of construction. The device can be operational in any place in the world with cellular coverage protecting people world-wide. 100% Open Source When developing this project, I ensured that all assets used, libraries and others, were open source to ensure that the application could be developed and released as soon as possible without bureaucracy. This project is fully open source and available on GitHub. Data Security The application involves the collection of user location information and its processing. All communications performed between the frontend and backend of the application are encrypted to prevent man-in-the-middle type attacks. Azure IoT Hub is also considered to have state-of-the-art security. Going Further While developing this project, numerous ideas to further develop and enhance the product came to mind, this section details them: Collection of blood oxygen level can be implemented without the need to change any hardware as this value can be extracted from the existing heart rate sensor. The SpO2 levels in the blood are an indication of the damage done by the virus. The development of a 3D printed enclosure would be preferable in a future iteration. The size of the device can also be reduced dramatically making it even more comfortable to wear. Market Research Many countries have been implementing alternatives to the monitoring of patients with coronavirus while they self-isolate at home. Taiwan has implemented a revolutionary tracking system where the patients are tracked via their mobile phone to ensure that they stay at home. Other countries have also implemented ideas to monitor the health of people in self-isolations and some systems work better than others. But no product collects both the vital information about the patient’s state and his/her location in a small, comfortable package. Target Audience This device is aimed at people that are sent by the hospital at home to self-isolate because they have been tested positive for a weak form of the virus or are asymptomatic. Benefits of using SmartWristband Ensuring that patients sent to self-isolate are staying at home Monitoring the patients’ vitals without the need of them being in hospital Liberating space in hospitals for people with severe manifestations of the virus Alerting doctors to the state of all patients in self-isolation 25/7 Providing a comfortable monitoring solution for the patient Providing the hospital with a forecast of the patient’s health Informing the patient about their health through a mobile and desktop dashboard Cost effective and scalable Project Conduct This section will guide you through the construction of the project. Step 1: Getting everything together The first thing we need to do is get all the components needed together. The components and services needed are listed in the BOM above. Figure 10: An image depicting all the components required for the projectUse the tutorials linked below to set up the software tools necessary for the project. Get the Arduino IDE or use the Web Editor Create your Hologram account and connect your SIM cardCreate a Microsoft Azure accountCreate a Power Bi account Step 2: Working with the MKR GSM Before we start making the project itself, we need to configure the MKR GSM to connect to Azure IoT. For this, we need to generate and store a certificate on the device to be able to verify the connection with the backend. There is a tutorial on Hackster that covers this for the MKR NB. Please follow along with this tutorial from the start and note that you should stop after you generated the certificate. Please ensure to save the SHA1 string as we will need it later. The tutorial is here. Step 3: Connecting everything together The next thing we must do is get everything wired up. Below is an image depicting the schematics for creating this project. Note that your components probably do not look like the ones in the schematics. Ensure that you connect the temperature sensor to A4 on the device and the heart rate sensor to A5. Don’t forget to put the SIM in! Figure 11: A diagram of the schematics for the SmartWristband deviceStep 4: Onto the IoT Hub Ok, now that we have all of that done, we can move on with preparing the IoT hub. We will be working in the backend for the next few steps to get that out of the way first. Ensure that you have an Azure account before continuing. The first thing you need to do is navigate to your console (portal.azure.com) and click on the create a resource button at the top left of the screen. Now type IoT Hub and select the option from the dropdown. Click on create after the setup was completed. Note that in this example, we will be using a free tier IoT hub so that we will not be charged for its usage. If deploying this solution, consider changing the tier to S1 (or S2/S3 depending on the scale). Create a new resource group and name your IoT hub. Now click on the Size and Scale option from the steps above. Now click Review and Create and deploy the resource. Wait for the IoT Hub to create and then open it by clicking onto All Resources from the menu on the right of the screen. We now need to create a device and attach it to the IoT hub. Navigate to the IoT Devices option on the menu on the right of the screen and click on the option. Click on the New button to add a new device to the IoT hub. Input the following credentials: Figure 12: A screenshot of the device tab in IoT HubMake sure you replace the Primary Thumbprint and the Secondary Thumbprint with your SHA1 value extracted in the second step of the project conduct.Click save and we are ready to go!Step 5: Creating the Cosmos DB DatabaseNow we need to create the database where the data sent by our device will be stored. I am using Azure’s Cosmos DB as it is accustomed to storing JSON files which is what we are sending from the device.Firstly, navigate back to the Create a Resource button from the menu on the right and click it. Search for Cosmos DB and then select the option.Select the resource group created with the IoT Hub and give it a name, keep the rest of the settings the same. Do ensure that the region is the same on both the IoT hub and the database to prevent region transfer costs.And that’s it! Wait for the resource to deploy and then we are ready to move on!Step 6: Creating the Streaming Analytics JobSo now that we have our IoT hub and database set up, we need to connect the two together so that the data inputted into our IoT Hub is streamed into the database as it is received. Start off by creating a new resource by typing Stream Analytics Job. Now select the resource group used up until now and ensure that the number of streaming units is set to 1. If delivering a high quantity of devices, you may want to consider creating more streaming units to handle the greater number of devices.Wait for the resource to deploy and then select it from the All Resources button on the menu on the left.Now that we are in the resource, select the Inputs button from the menu on the left to select our input. Click on Add Stream Input and then select IoT Hub from the list of options.Enter the name of your IoT hub and then select it from the menu shown. Do not change any other settings. Click Save. Now click on the Outputs option from the menu on the left of the screen and select the Cosmos DB option from the list provided.Name the output and then select the database from the options provided. Select Create New under Database and set the database name to SmartWristband and the container name to data. Leave the document ID empty. Now click Save.The final thing we need to do is click on Query from the options. We need to supply the service with code to route all the data from the IoT hub into the database. Copy and paste the code below into the space provided. The code will map all inputted values to outputs which will then be stored in a JSON format in the Cosmos DB.SELECT time as time, id as name, geoLat as latitude, geoLng as longitude, isWorn as isWorn, heartrate as heartrate, temperature as temperature, battery as battery INTO [universum-smartwristband-db] FROM [universum-smartwristband-hub] After that is done, click on the Save Query button from the menu at the top of the screen and we are ready to go. Now all we need to do is click back on Overview from the menu on the left and then start the streaming by pressing the Start button.Step 7: Libraries RequiredAll libraries used in this project are open source. Below is the list of all libraries used and the links to their GitHub repositories. Please make sure you download and install them before moving on.MKRGSM Library - https://github.com/arduino-libraries/MKRGSM RTCZero LibraryArduino Bear SSL Library ArduinoECCX08 Library Arduino MQTT Client Library Arduino Low Power Library DFRobot Heartrate Library Step 8: Preparing the Variables Now we can focus on the frontend of the application. Open the code from the GitHub repo in the Arduino IDE or web IDE and follow along with the steps below to edit the variables in the document so that the MKR GSM will be able to connect to Azure IoT. The first thing we will need to do is navigate to the IoT hub created and copy the hostname shown. Now open the secrets.h file from the project and input the string into the SECRET_BROKER field. The next thing is getting the device name. This is simply the name given to the device in the IoT Hub. Copy the name displayed and then paste it in the SECRET_DEVICEID field in the secrets.h file. At the end, your file should look something like this. Figure 13: Inserting the credentials in the Arduino sketchThe last thing you need to do is change the DEVICE_ID. I included this feature so that all devices would have a specific ID when deployed. You can set the ID to the name of the patient or a string to be able to identify the devices and distinguish them.Finally, I want to talk about the MODE option. When I created this project, I needed to have a way to easily test and troubleshoot the application before deploying it. The mode of the application solves this. There are two modes in which the application can be set:DEVELOP_TIME is the developing mode. Here, the device prints verbose to the serial (the device only works connected to the computer with the serial monitor on). The device also wakes up and collects data every 10 seconds. RELEASE_TIME is the release mode. Here, the application works as expected, it can work on the field without the need of a connection to a computer, it will also take samples every 5 minutes as opposed to 10 seconds. We will toggle between these modes later, for now, leave it in DEVELOP_MODE. Step 9: Flashing the Developer Version Now that all the setup is done, we need to test the code out to ensure it is running in the DEVELOP_MODE. To do this, ensure that you follow all the steps above and then connect your device to your PC or mac via USB and then upload the sketch. Open the serial monitor (ctrl/cmd-shift-m) and view the verbose. It will take a while to configure the first time, ensure that the data is being sent to the IoT Hub correctly. Then visit the IoT Hub and check the graphs to see if data was received. You are now ready to deploy the application! If you need help troubleshooting, you can contact me by the email provided below. Step 10: Shipping the Release Version To change to the release version, all you need to do is change the MODE definition in the secrets.h file to RELEASE_TIME. Now upload this code to the device, ensure the LiPo battery is connected and then unplug it from the computer. You should see the onboard LED of the device flashing every 10 minutes indicating that a cycle is running. Check the IoT Hub and Cosmos DB database to ensure that the data is going through. Now you are ready to deploy the device! Ensure you send some data to the backend before continuing as we will need this when creating the dashboard. Step 11: Onto the Dashboard In this section I will explain working with the data in the Power Bi dashboards and reports, I will not go over how to design the dashboard because this is up to personal preference but will link tutorials that show you how to do this in detail. Doctor Dashboard I will start with the doctor dashboard. Make sure you have Power Bi desktop installed on your PC. Mac users can use the Power Bi online version to create this report, everything is basically the same. Launch the application and click on the Get Data button. Now navigate to the Azure option and select Cosmos DB from the options. Now go to your Cosmos DB resource and copy the URI link and paste it in the field in Power Bi. Sign in if this is required. Now we need to go to the keys window in the Cosmos DB dashboard and copy the PRIMARY KEY and paste it into the Account Key field. Now navigate through the database and ensure that the data file is checked. Click load and then we are ready to go! Now that you are in the report, find the Transform data button from the menu at the top of the screen. Click it to get a table with data. Click on the button next to the title of the table and select the fields shown above. You should see your table expand. Now we need to change the data types of the rows. Identify the Data Type button from the menu at the top of the screen and change the values accordingly. Now click on Close and Apply and you will be brought back to the dashboard. Your dashboard should look something like this. Figure 14: Screenshot illustrating the data points in the Power Bi reportThe next thing we will need to do is create measures to process data and convert it into different forms in the report. Open the Stream Analytics Script folder from the GitHub repo in Visual Studio code. I installed an extension called DAX for Power Bi to get context highlighting. There are a number of files which have to be edited specifically for the patient as they hold the patient’s information. The list of files that must be edited is below: Gender.dax Age.dax Address.daxOpen these files in VS code and edit them there. Now we will create new measures in Power Bi using these files. To do so, open the Power Bi report and click on the New Measure button from the menu at the top of the screen. Copy and paste the first file’s content into the text bar. Ensure that the Format and Data Category are set accordingly (i.e. set the category of latitude data to latitude). Now repeat this step for all other files, creating a new measure for each. Now we are moving on to the fun part – designing the dashboard. Please look at the tutorials below to get an idea of how to create infographics and style the dashboard: Basic Power BiComplete Guide to Power Bi Free Udemy Course on Power Bi Forecasting data (ML) in Power Bi (used on temperature, heart rate and battery level) Now after the dashboard is designed, we need to publish it on the web so that we can access it from anywhere, on any device. Note that the data in the report is automatically refreshed when the user opens it (there is also a refresh button). Click on the Publish button from the menu at the top of the screen and select My Workspace as the destination. Wait for the dashboard to upload. To continue working on this, open the Power Bi report in the browser. We will now be working on the dashboard that summarises all patients. To do this, click on the tile depicting the status of the patient to see a menu. From the menu, select the pin visual button and create a new dashboard. This visual will pin to the dashboard. Repeat this for the following cards: Name Status Temperature Heart Rate The doctor will be able to see a glimpse of all the patients being monitored on this dashboard. Finally, click on the temperature card in the dashboard and then on the menu button, select the Manage Alerts button to open a menu where you can set alerts for the visual. Configure this as below and repeat the step with heart rate (set the threshold to 100). And that’s it, we now need to work on the patient dashboard.Patient DashboardWe will start this dashboard by copying the doctor dashboard as we will be using all the measures and data collected there but display it in a different way. I kept all the data there but removed the forecasting for the temperature and heart rate sections (to prevent patients from worrying too much about it) and removed the location section (because the patient knows where they are). I also developed a mobile version of this dashboard. To do so, navigate to the View menu and then select Mobile Layout. From there, we only need to drag and drop the existing tiles onto the mobile phone to create this layout. After this is done, we will upload the dashboard online again as done before. This dashboard can be shared with the patient through the Power Bi app where they can get a mobile version of the application showing them all the information they need as well as an online view.Step 12: Finally, the enclosure So now that everything is done, we need to create an enclosure for the project, now ideally it would be 3D printed, but because I don’t have a 3D printer (I really need to get one), I cut pieces of plastic out and assembled them that way. I do though have a 3D design made for the enclosure of the prototype. The device is quite big in this instance and a future and industrial version will obviously be reduced in size (I just didn’t want to solder all the components onto a PCB so I could reuse them in future projects). And that’s it! The project is done!Conclusion SmartWristband is a compact wearable device which monitors a coronavirus patient’s temperature, heart rate and alerts authorities should they violate their lockdown requirements. The information can be viewed to both patients and doctors on a minimal dashboard powered by Microsoft Power Bi. I was inspired by the Taiwanese government because of their smart tracking devices that ensure that people confirmed with the virus stay at home and abide by the rules of the quarantine. I felt like this system could be improved to further enhance the safety of the patient by also monitoring their heart rate and temperature while at home. Coronavirus is a tricky problem to tackle and truly needs a lot of cooperation and devotion to overcome. I believe that this application is implementable at global level to help monitor the health of patients confirmed with weak forms of the virus allowing them to stay at home and liberate space in hospitals that can be assigned to more urgent cases. The thing I enjoyed the most out of the making of this project was the dashboard, I really enjoyed designing it (I am a visual person). I encountered some problems connecting the Arduino MKR GSM to Azure IoT. This was because I set the expiry date of the device’s certificate to something like 2 minutes (took me a while to realise).

Brainy is a beautiful PCB pin badge, it is shaped like a brain and it has a funny face with a band-aid. Wear it and shine everywhere!It has 8 charlieplexed white Led's, 6 on the front and 2 on the back. They simulate the neurons activity. It is powered with a CR2032 battery and has a button to select the desired animation. Press it for change the animation or to turn it off (low power mode).Is controlled by a PIC12LF1822 and all the design files (Eagle PCB project and MPLAB firmware) are open source, so you can make your own animations and upload it with the built-in ICSP connector. Use your brain and customize your badge!!!I designed the PCB on Eagle with the help of Inkscape and svgtoeagle to get the image into the CAD software.PCBWay has done great job making the board, specially with the outline. I soldered the components with hot air and I used a stencil to apply the solder paste.Why I make it?I had a brain surgery on march 28 2020, I got a Ventriculoperitoneal Shunt due to a tumor in my tectal plate that was causing hydrocephalus. The tumor can't be removed, it's to risky. But with the valve I am going to be ok for a while. Some people helped me get through this, so I made this badge for thanking them in the most memorable way I could think.My family and friends also helped me with the emotional support I needed. As an introvert it is hard to me to say "Thank you" in a deeper way. So I used my abilities to materialize this feeling in a PCB Badge.Read the full story on HackadayThanks!

Kawaii means cute in Japanese we based this project on KawaiiTech logo. This pendant is so cute, easy to assemble and re-program which makes it totally customizable, it can be worn as pendant or even earrings. We liked black solder mask with HASL finish, maybe you wanna rock ENIG?The board is based on ATTINY85 charlieplexing 6 LEDs and powered by a CR1220 battery. BOM:1 ATTINY85 SOIC 86 0805 LEDs we recommend ultra bright1 cap 0805 0.1uF1 CR1220/12225 battery holder, footprint is made for 2894 but should also work with S8201-46R.1 Switch CUS-12TBYou can generate an Arduino Project and use Arduino UNO board to program it. Or if you have the ICE Atmel programmer use the on board footprint.https://www.youtube.com/watch?v=Bx5GLyJSWPk

### DESCRIPTIONHi, everyone, this project is a wearable wich main function is a watch, but at the same time it can be a development board for other applications or gatgets. The main idea, is to have a very small (35mm x 35mm) wearable board that could be used with a battery. It's based on the Atmega328P microcontroller.Hola a todos, este proyecto es un wearable cuya función principal es la de un reloj de pulsera, pero al mismo tiempo puede ser usado como una tarjeta de desarrollo para otras aplicaciones o gatgets. La idea principal es tener una muy peque?a (35mm x 35mm) tarjeta wearable que pueda ser usada con una batería. El circuito está basado en el microcontrolador Atmega328P.### TECHNICAL DETAILS / COMPONENTSThe electronic design is based in a generic Arduino Nano with a CH340 USB controller, but with some modifications, so it can be operated at 3.3/3.7 volts, this way it can be powered with a small rechargable lithium battery. Other periphals can be conected trought the 6 analog I/O with the J3 connector or with the SPI protocol throught the J1 conector. The follow diagram show the base circuit.El dise?o electrónico está basado en un Arduino Nano genérico con un controlador USB CH340, pero con algunas modificaciones, de tal manera que pueda ser operado a 3.3/3,7 voltios, de esta manera pueder ser alimentado con una peque?a batería recargable de litio. Otros periféricos pueden ser conectados a través de las 6 Entradas/Salidas analógicas a través del conector J3, o con el protocolo SPI mediante el conector J1. El siguiente diagrama muestra el circuito base.Half of the device is an Arduino Nano and the other half is the clock style LED array. The follow diagram show the LED array and the connection with the Atmega328P.La mitad del circuito es un Arduino Nano y la otra mitad son los led con arreglo en forma de reloj. El siguiente diagrama muestra la manera en que están organizados los leds y la conexión con el Atmega328P.The follow image shows the expansion conectors pinout.La siguiente imagen muestra la disposición de los pines de los conectores.BILL OF MATERIALSC1 - 10ufC2 - 100nfC3 - 100nfC4 - 100nfC5 - 10ufC6 - 100nfC7 - 100nfC8 - 22pfC9 - 22pfC10 - 22pfC11 - 22pfD1:D16 - LEDPWR - LEDJ1 - Conector USB(UX60SC-MB-5ST)J2 - Conector(FH12-8S-1SH)J3 - Conector(FH12-6S-1SH)R1 - 1kR2 - 1kR3 - 10kR4 - 1kR5 - 1kR6 - 1kR7 - 470RR8 - 470RR9 - 470RRPWR - 470RS1 - Switch(B3U-wB)SL - B3SLSM - B3SLSR - B3SLU1 - Atmega328P (QFP-32 9x9x0.8)U2 - CH340 (SOP-16 7x1.27)U3 - LM7805 (SOT-89)U4 - MMBT3904 (SOT23)U5 - MMBT3904 (SOT23)U6 - MMBT3904 (SOT23)Y1 - 16Mhz CrystalY2 - 12Mhz Crystal### LEARN / TOPIC / BUILD INSTRUCTIONSFor the energy save the power led can be omited. WARNING: This PCB is a prototype and wasn't test. The test was made with a protoboard and an Arduino Nano. Also, the LEDs are placed in counterclockwise direction. The code showed below works with this configuration.Para ahorrar energía el led de encendido puede ser omitido. PRECAUCIóN: Este PCB es un prototipo y no ha sido probado. La prueba se realizó con un protoboard y un Arduino Nano. También, los leds han sido puestos en contrareloj. El código que se muestra a continuación funciona con esa configuración.Also, I designed a box that can be made with a 3D printer. The STL files are liested bellow.También, he dise?ado una caja que puede ser hecha con una impresora 3D. Los archivos STL se muestran abajo.DropBox STL file1 - BoxDropBox STL file2 - Cover### CODE// DuinO'Clock// 22/Nov/2018// Benjamín Alejandro Luna Ramírez// Versión 1.1#include <avr/sleep.h>// Constantsconst byte Button_Left = 2;const byte Button_Center = 3;const byte Button_Right = 4;const byte T1 = 5;const byte T2 = 6;const byte T3 = 7;const byte Led_Circle_Start = 7;const byte Preescaler_Divider = 7; // 7 = 128 times.const byte Preescaler_Frequency = 128;const int Time_Run = 500 / Preescaler_Frequency; // Time the leds are on when the device turn on.const int Time_Led_Blink = 400 / Preescaler_Frequency;const int Time_Led_Between = 200 / Preescaler_Frequency;// Variables globalesbyte volatile timeHour = 1;byte volatile timeMinute = 0;byte volatile timeSecond = 0;int volatile timeMiliseconds = 0;/* currentFunction values are: 0:none 1:Showing Hour 2:Changing Hour*/byte volatile currentFunction = 0;void setup() { // put your setup code here, to run once: CLKPR = 0b10000000; CLKPR = Preescaler_Divider; // Buttons pinMode(Button_Left, INPUT_PULLUP); pinMode(Button_Center, INPUT_PULLUP); pinMode(Button_Right, INPUT_PULLUP);// Transistors pinMode(T1, OUTPUT); pinMode(T2, OUTPUT); pinMode(T3, OUTPUT);// Leds pinMode(Led_Circle_Start + 1, OUTPUT); pinMode(Led_Circle_Start + 2, OUTPUT); pinMode(Led_Circle_Start + 3, OUTPUT); pinMode(Led_Circle_Start + 4, OUTPUT); pinMode(Led_Circle_Start + 5, OUTPUT); pinMode(Led_Circle_Start + 6, OUTPUT);// Enciendo los leds menos significativos en secuencia para indicar que está encendido. digitalWrite(T3, HIGH); digitalWrite(Led_Circle_Start + 1, HIGH); delay(Time_Run); digitalWrite(Led_Circle_Start + 1, LOW); digitalWrite(Led_Circle_Start + 2, HIGH); delay(Time_Run); digitalWrite(Led_Circle_Start + 2, LOW); digitalWrite(Led_Circle_Start + 3, HIGH); delay(Time_Run); digitalWrite(Led_Circle_Start + 3, LOW); digitalWrite(Led_Circle_Start + 4, HIGH); delay(Time_Run); digitalWrite(Led_Circle_Start + 4, LOW); digitalWrite(T3, LOW);// Disable interrupts before changing the preescaler value. noInterrupts();// Synchronous mode. ASSR = (ASSR & 0b11011111);// Operate in CTC mode and preescaler. TCCR2B = 0b00000111; TCCR2A = 0b00000010; TCNT2 = 0;// 10 milisegundos (16,000,000 / 1024 * 0.01) = 156 OCR2A = 255; TIMSK2 = 0b00000010; interrupts(); SleepDevice();}void SleepDevice(){// Attach the interrupts to the pins. attachInterrupt(digitalPinToInterrupt(Button_Center), ShowHour, LOW); attachInterrupt(digitalPinToInterrupt(Button_Left), ChangeHour, LOW);// Enter Power-Save Sleep mode. SMCR = 0b00000111; sleep_cpu();// Disable sleep after waking up and detach interrupt. SMCR = 0b00000000; detachInterrupt(digitalPinToInterrupt(Button_Center)); attachInterrupt(digitalPinToInterrupt(Button_Left), ChangeHour, LOW);}void loop() { switch(currentFunction) {// Showing the hour. case 1: LightHour(); delay(Time_Led_Blink); ClearLeds(); delay(Time_Led_Between); LightMostSignificantMinute(); delay(Time_Led_Blink); ClearLeds(); delay(Time_Led_Between); LightLessSignificantMinute(); delay(Time_Led_Blink); ClearLeds(); currentFunction = 0; break;// Changing hour. case 2: byte next = 0;// Changing hour// Wait for the button. while(digitalRead(Button_Left) == LOW) { delay(1); }// >> Show the current hour. LightHour(); while(next == 0) { // Probes if one of the buttons has been pressed. if(digitalRead(Button_Left) == LOW) { next = 1; while(digitalRead(Button_Left) == LOW) { delay(1); } }else if(digitalRead(Button_Right) == LOW){ if(timeHour <= 11) timeHour++; else timeHour = 1;// >> Show the current hour. LightHour(); while(digitalRead(Button_Right) == LOW) { delay(1); } } } next = 0;// >> Show the current most significant minute. LightMostSignificantMinute();// Changing most significant minute. while(next == 0) {// Probes if one of the buttons has been pressed. if(digitalRead(Button_Left) == LOW) { next = 1; while(digitalRead(Button_Left) == LOW) { delay(1); } }else if(digitalRead(Button_Right) == LOW){ if(timeMinute < 55) timeMinute += 5; else timeMinute += 5 - 60; LightMostSignificantMinute(); while(digitalRead(Button_Right) == LOW) { delay(1); } } } next = 0;// >> Show the current less significant minute. LightLessSignificantMinute();// Changing less significant minute. while(next == 0) {// Probes if one of the buttons has been pressed. if(digitalRead(Button_Left) == LOW) { next = 1; while(digitalRead(Button_Left) == LOW) { delay(1); } }else if(digitalRead(Button_Right) == LOW){ if((timeMinute % 5) < 4) timeMinute++; else timeMinute -= 4; LightLessSignificantMinute(); while(digitalRead(Button_Right) == LOW) { delay(1); } } } ClearLeds(); currentFunction = 0; break; } SleepDevice();}void LightHour(){ ClearLeds();// Show the led for the hour. byte column = T2; byte mostSignificantLed = 0; if(timeHour == 12) { mostSignificantLed = 6; }else if(timeHour > 5){ column = T1; mostSignificantLed = 12 - timeHour; }else{ mostSignificantLed = 6 - timeHour; } digitalWrite(column, HIGH); digitalWrite(mostSignificantLed + Led_Circle_Start, HIGH);}void LightMostSignificantMinute(){ ClearLeds();// Show the leds for the minutes. byte column = T1; byte mostSignificantLed = 0; if(timeMinute < 5) { column = T2; }else if(timeMinute >= 30){ column = T1; }else{ column = T2; } mostSignificantLed = timeMinute / 5; if(mostSignificantLed > 5) { mostSignificantLed = 12 - mostSignificantLed; }else if(mostSignificantLed == 0){ mostSignificantLed = 6; }else{ mostSignificantLed = 6 - mostSignificantLed; } digitalWrite(column, HIGH); digitalWrite(mostSignificantLed + Led_Circle_Start, HIGH);}void LightLessSignificantMinute(){ ClearLeds(); byte mostSignificantLed = timeMinute / 5; byte lessSignificantLed = timeMinute % 5; if(lessSignificantLed > 0) { if(lessSignificantLed < 4) lessSignificantLed = 4 - lessSignificantLed; digitalWrite(T3, HIGH); digitalWrite(lessSignificantLed + Led_Circle_Start, HIGH); }}void ClearLeds(){ digitalWrite(T1, LOW); digitalWrite(T2, LOW); digitalWrite(T3, LOW); digitalWrite(Led_Circle_Start + 1, LOW); digitalWrite(Led_Circle_Start + 2, LOW); digitalWrite(Led_Circle_Start + 3, LOW); digitalWrite(Led_Circle_Start + 4, LOW); digitalWrite(Led_Circle_Start + 5, LOW); digitalWrite(Led_Circle_Start + 6, LOW);}ISR(TIMER2_COMPA_vect){ timeMiliseconds += 2088; if(timeMiliseconds >= 1000) { while(timeMiliseconds >= 1000) { timeMiliseconds -= 1000; timeSecond++; } if(timeSecond >= 60) { timeSecond -= 60; timeMinute++; if(timeMinute == 60) { timeMinute = 0; timeHour++; if(timeHour == 13) { timeHour = 1; } } } }}void ShowHour() { detachInterrupt(digitalPinToInterrupt(Button_Center)); detachInterrupt(digitalPinToInterrupt(Button_Left)); currentFunction = 1;}void ChangeHour() { detachInterrupt(digitalPinToInterrupt(Button_Left)); detachInterrupt(digitalPinToInterrupt(Button_Center)); currentFunction = 2;}

### DESCRIPTIONThis badge has been designed to hold a family workshop where children and their families will learn a little about the maker world and electronics. The workshop is organized by the open nonprofit community Ripolab Hacklab of Ripollet (Barcelona) and the workshop is organized by the City Council of Sabadell (Sabadell, near Barcelona).### TECHNICAL DETAILS / COMPONENTSThe graphic design has been done in Inkscape and the design of the PCB circuit has been done in KiCAD.More detail in http://akirasan.net/badgelife-la-torre-de-laigua/Components:x1 ATTiny85x1 zócalo 8 pinsx1 push buttonx1 resistor 10Kx2 LED RGB WS2812 5mmx1 switch on/offx1 socket battery CR2032x1 Battery CR2032### LEARN / TOPIC / BUILD INSTRUCTIONSThe Torre de l'Aigua is a Modernist water reservoir considered one of the most emblematic buildings of the city Sabadell. Its construction began in 1916 and ended in 1918, this year celebrates a centenary (ideal to pay tribute). It worked as a warehouse between 1922 and 1967, and is considered one of the 100 elements of the Industrial Heritage of Catalonia.

Have you ever thought of making a badge-sized PCB that can display some letters, numbers, etc... or your name?In this project, I will be showing how I built a badge-sized ATtiny85-based LED matrix display (5x4 matrix). I have used Charliplexing technique for driving 20 LEDs using ATtiny85.Link to Documentation:This project is open source. If you would like to build your own, all of the resources are available in the GitHub.https://github.com/amalmathewtech/ATtiny_LED_Matrix_Display_Badge

I decided sometime last year that I wanted to make a smart watch from scratch. I am an electrical engineer and product designer by day, so this was a fun side project that had been rolling around in my head for a while now.For more info on the build process, click here.

GRINTCH XMAS BADGEScary the cuddly? we don't know how to saythis is a PCB badge from the greenest cute Christmas monster.The leds under the eyes and details on the hat give all the charm to the project.

The Light Badge is an electronic kit which utilizes an LDR (light dependent resistor) to detect lowering light levels and light a LED once it gets dark.This is a great example of an LDR in action.An LDR (light dependent resistor) or photoresistor is a resistor where the resistance decreases with the strength of the light.Schematics:This is how the circuit works: When exposed to bright light, the photoresistor’s resistance is very low.It drops to around 20-30 KΩ.Current travels through the 100 KΩ resistor and then has 2 paths.It can either go through the base of the transistor or go through the photoresistor. The base of transistor to the collector has a resistance of around 400 KΩ.Current always takes the path of least resistance. When photoresistor is exposed to bright light, its resistance is about 20-30 kΩ, which is significantly less than the 400 kΩ of resistance the base of the transistor has.Therefore, most of the current will go through the photoresistor and very little will go to the base of the transistor. So the base of the transistor is bypassed, Thus, the transistor does not receive enough current to turn on and power on the LED.Thus the LED is off when there is lot of light in the surroundings.When it is dark, photoresistor’s resistance becomes very high.It’s resistance goes up to 2 MΩ.This creates a very high resistance path, due to this, most of the current will go through the base of the transistor. Means that current does not go through the photoresistor when it is dark.In the above circuit LDR and the 100 k resistor form a simple ‘potential divider’ circuit, where the middle point of the potential divider is fed to the base of the NPNtransistor. Therefore based on light intensity the brightness of LEDs will be changed.Note: On the PCB I have represented anode of led with small white dotted silkscreen.All the Project files are up on GitHub, go make!This project is Certified with OSHWA (OSHWA UID IN000009)https://github.com/tinkererway/Light-Badge

Soldering can seem a bit daunting, but it is easier than it looks and it is a skill that opens a world of DIY projects to you. This project is the perfect way to not only learn how to solder, but to show off your new found skill to your friends and family.Unlike other simple soldering project, this one will also teach you about circuits, and how they work. And it has a switch to save the battery. More power to you!Feel free to contact me for a custom badge for your group or event!I have pannelized them in a 100 x 100 mm sheet to minimize manufacturing cost. This means if you order 5 boards, you will get 5 x 9, or 45 individual boards. Use the following settings when ordering:-Board Type: "Pannel by Customer".-Route Process: "Pannel as tab route".-Accept X-outBill of Materials:- 1 ea., PCB- 1 ea., SW1 SWITCH SLIDE SPDT, C&K JS102011SAQN, https://www.digikey.com/short/j58qp5- 1 ea., RES 100 OHM 1/4W 5% AXIAL, - 1 ea., 5mm RGB Multicolor Slow Flashing, http://a.co/d/8MpfUT4- 1 ea., CR2032 Batt retainer, Linx BAT-HLD-001-THM, https://www.digikey.com/short/ppdw43- 1 ea., Tie Tack & clutch, https://www.dhgate.com/product/10mm-post-nails-post-gold-silver-brass-tie/391539398.html- 1 ea., CR2032 Battery, Panasonic CR2032, Digikey P189-ND (requires ground shipping, or buy locally).Assembly Video:?

This is a tiny electric violin powered by an 3V CR1220 battery and controlled by an ATtiny85 microcontroller. It uses a piezoelectric buzzer to make sounds when the four strings are touched. It does this by reading random values through an analog pin connected to the strings.It also features two side view LEDs on the back which are meant to shine through the PCB to light up the two F-hole symbols of the violin when sound is played.It also has a push-button for turning it on/off when long presse or for switching through different songs or functioning modes (preset songs, light only or sounds based on values read through the strings).I also added two pads to which sewing hooks can be soldered, so the PCB can be also used as a badge.

What's this?This is DIY driver for flashlights with brigh LEDs, such as CREE XM-L, XP-G and others. It is created as replacement for default LED driver in your headlamp.Driver firmware is open-source, so you can modify it on your own anytime.Even without programming skills you can set up all working parameters just by editing definitions in .h file.Or you can flash .hex file with default parameters. For firmware upload you will need Arduino or any ISP programmer, such as USBASP.Benefits:- ON/OFF with single button click (tact switch button). This was a main reason why i made this project.- Working voltage: 2.3V - 5.5V, 4A maximum current (with SI2323 mosfet).- Extremely low power consumption at moonlight mode: only 5mA with XM-L led. With standart 18650 cell it will beam more than 20 days.- Stepless brightness adjustment with gamma-correction, from moonlight to turbo. Brightness level is remembered for the time of shutdown.- Battery voltage control with power-off when battery is discharged.- Two additional modes - emergency beacon and strobe. Additional led for backlighting.- Reverse polarity protection and ESD protection.Also, this driver is wery compact (25 х 12.5 mm / 1 x 1/2 inches), so it can be installed in many headlamps or other devices. Partlist contains 10 required components (Attiny13, mosfet, resistors, diode and capacitor) and 5 additional (ESD protection diodes and smd led). All source code and documentation can be found on github.

This article is proudly sponsored by PCBWAY.PCBWAY make high quality prototyping PCBs for people all over the world. Try it for your self and get 10 PCBs for just $5 at PCBWAY with very great quality, Thanks PCBWAY. The Robadge#1 that I developed for use in this project uses PCBWAY PCB services. In this instructables, I will show you how to build Robadge#1 LED Blinking Robot Badge. Let's get started!?The leg hole for the resistor on the PCB is designed for a size 1/6w resistor, but you can also use a size 1/4w resistor by bending the leg on one side then insert to PCB board as shown in the picture.You can insert other components such as Transistors, Capacitors and Switch following the sign on the PCB board.Insert the LEDs, ensuring the short legs are towards the centre of the board. Turn the board over and solder all legs components.?Using your cutters it’s time to snip the legs from the components. You should wear eye protection as the legs can fly off!Place the battery holder into the provided holes from back of PCB.Turn the board over again then solder the legs in place.Using your pliers hold the pin back onto the centre of the pad. Tin your soldering iron then hold the tip down with the pliers heat the pin back and hold the iron in place until you notice the solder flow to the edge.?Insert the battery writing side facing out.Write the name you want, using permanent marker on the white area below the PCB.Slide the switch lever to the right ON position.?Hopefully you enjoy your Robadge#1. If you do, please share your makes, share the link, like and subscribe Instructables & Youtube. As always, if you have any questions please let me know!https://www.pcbway.com/?from=bluino

### DESCRIPTIONThe board is designed to develop a Brain Computer Interface(BCI) equipment at gathering the EEG(Electroencephalography ) signals from Human brain. actually I aimed to desing BCI daisy board as shield for my previous BCI board, which it is based on SPI daisy chain commnucation topology and its name comes from, but it can be used interfacing any MicroController via SPI comm. it has 8 bio-potantiel signal(EEG,EMG,ECG,EOG,etc.) channels, on board 2.048MHz osc. and some connectors.### TECHNICAL DETAILS / COMPONENTSthe board is based on ADS1299 24bit AFE ADC ### LEARN / TOPIC / BUILD INSTRUCTIONS

This is the firts version of the 5th anniversary badgeI think in black color + gold mask could be awesome!!!It's a 100% opensource project. All info and files are in the Github link (description)