Billions and Billions

The open data platform for the Internet of Things


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CollectCollect

Send sensor data to the cloud.

AnalyzeAnalyze

Analyze and visualize your data.

ActAct

Trigger a reaction.




ThingSpeak Features

  • Real-time data collection and storage
  • MATLAB analytics and visualizations
  • Alerts
  • Scheduling
  • Device communication
  • Open API
  • Geolocation data
  • Available on GitHub
  • Works With

  • Arduino
  • Raspberry Pi
  • Electric Imp
  • Mobile and web apps
  • Twitter
  • Twilio





  • Latest News

    Analyzing CheerLights with MATLAB

    CheerLights is an Internet of Things project created by Hans Scharler that allows people’s lights all across the world to synchronize to one color set by Twitter. This is a way to connect physical things with social networking experiences and spread cheer at the same time. When one light turns red, they all turn red.

    CheerLights uses ThingSpeak to collect the latest color. We get the color value by following “CheerLights” on Twitter using the TweetControl app. When someone Tweets using “CheerLights” and a color name, the TweetControl app writes the color to the CheerLights Channel on ThingSpeak. Other developers wanting to join the CheerLights project read in the latest color value using the ThingSpeak Channel API and then set their light color to the same one.

    With some MATLAB Analysis and Visualizations, I know that currently red is the most popular color on CheerLights! I have recently taken advantage of the MATLAB integration with ThingSpeak. Under Apps -> MATLAB Analysis, we have an example that will show you how to analyze the public CheerLights Channel on ThingSpeak to determine the most requested color. The MATLAB Analysis example is called, “Analyze text for the most common color”.

    People all over the world have joined CheerLights by making all kinds of light displays, apps, and browser plugins. I recently created a CheerLights display for my parents using a LIFX Wi-Fi Light Bulb. If you want to control all of the lights, just send a Tweet using Twitter that mentions @CheerLights and a color.

    “@CheerLights Let’s go Blue!”

    Check out CheerLights.com for more detail and for ideas on how to join the project. We are all connected!

    [via CheerLights.com]


    You’ve Collected Lots of IoT Data, Now We Can Help You Figure Out What It Means!

    For the last several years, I have been collecting data with ThingSpeak from devices all around my house. I have been tracking temperature, humidity, light levels, outside weather data, my deep freezer’s temperature, the state of My Toaster, and air quality metrics. I just recently started to think about what all of this data really means to me and if it’s good data to begin with. Wouldn’t it be great if I could explore my data in ThingSpeak?  Well, I am happy to say that with the latest upgrade to ThingSpeak, you can do just that.

    We have been working with the MATLAB team at MathWorks to provide two new ThingSpeak Apps: MATLAB Analysis and MATLAB Visualizations. With these new built-in Apps, the ThingSpeak web service can automatically run MATLAB code. That makes it easier to gain insight into your data.

    With the MATLAB Analysis app, I am now able to turn my home’s temperature and humidity data into dew point. Dew point is important to find out if the environment is comfortable independent of just knowing the temperature alone. If the dew point is too high or too low, your guests may notice their glasses sweating or that they are uncomfortable.

    I am also able to clean up my sensor data and filter out bad data and write it back to a new ThingSpeak channel. From time to time, I see one of my sensors report a really high value, and I’d like to have a way to fix it.

    We have provided many MATLAB code examples to get started quickly.

    Some of our analysis examples include:

    • Calculate Average Humidity
    • Calculate Dew point
    • Convert Celsius to Fahrenheit
    • Eliminate data outliers
    • Convert Fahrenheit to Celsius
    • Calculate hourly max temperature
    • Replace missing values in data

    With MATLAB Visualizations, we made it way easier to chart data from multiple data fields. By selecting the “Wind Velocity” example MATLAB Visualization, I can see a plot of the wind velocity data collected by my weather station.

    Other visualization examples include:

    • View temperature variation over the last 24 hours using a histogram
    • Plot wind velocity over the last hour using a compass plot
    • Understand relative temperature variation
    • Plot data from multiple fields
    • View temperature and pressure levels
    • Visualize relationship between temperature and humidity

    Are you looking for an easy way to connect your Arduino or Raspberry Pi devices to ThingSpeak? We have also been working with the MATLAB team at MathWorks on some Hardware Support Packages to help with that. I’ll talk about that in a future blog!

    This is really big news for the ThingSpeak Community. I am really excited to see what you do with these new apps. I will share projects on the blog as they come in. Let’s find out together what all of this data means. Get started at ThingSpeak.com!

     


    [Kickstarter] nodeIT – Small, Stackable IoT Device

    Kickstarter projects pop up all of the time. Developers are looking to raise money for their projects so they can order a larger production run and gauge market reaction. A lot of recent projects are trying to address the “Maker Community” by making it easier to prototype connected devices and sensors. We just found one called, “nodeIT” from Sweden.

    The nodeIT is centered around the ESP8266 Wi-Fi microcontroller and allows you stack other boards to extend its base functionality. Once the nodeIT is connected to your Wi-Fi network, you can easily publish data to ThingSpeak and visualize the results, such as data collected by a barometric sensor.

    For more information about nodeIT, follow their Kickstarter campaign and check out their ThingSpeak Room Monitor project.

    [via Kickstarter]



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