Statistics and Machine Learning Toolbox

Signal Processing Toolbox

When you are logged into ThingSpeak using your MathWorks Account, you can use functions from the following toolboxes if you are licensed to use them:

With multiple sensors around my house or office, I want to be able to send data to multiple ThingSpeak channels. But, when I want to perform data analysis, I have a hard time working with data from multiple channels. The channels do not have the same time stamps and are out-of-sync with each other.

With R2016b of MATLAB^®, I am able to use the new timetable data container. Once the data is a stored as a timetable, I can perform powerful operations such as retime, synchronize, and rmmissing.

In this example, I have two sensors outside of my office here in Natick, MA. One sensor is a temperature sensor that is sending data to ThingSpeak channel 163540. My other sensor is writing humidity data to channel 163545. Both channels are public. My goal is to plot temperature versus humidity over one time series. To accomplish this, I will use timetable and synchronize inside of a new MATLAB Visualization on ThingSpeak.

% Read from the temperature channel
temperatureTT = thingSpeakRead(163540,'Fields',1,'NumPoints',100,'outputFormat','timetable');

% Read from the humidity channel
humidityTT = thingSpeakRead(163545,'Fields',1,'NumPoints',100,'outputFormat','timetable');

% Synchronize two timestables and fill in missing data using linear interpolation
TT = synchronize(temperatureTT,humidityTT,'union','linear')

% Plot Temperature and Humidity over time
plotyy(TT.Timestamps,TT.Temperature,...
       TT.Timestamps,TT.Humidity);
        
title('Temperature and Humidity Synchronized From Two Channels')
xlabel('Temperature and Humidity in Natick, MA')
legend('Temperature','Humidity')

The first part of the script reads in ThingSpeak data from two different channels and stores the data in two timetables. Once the data is stored in a timetable, I am able to take advantage of synchronize. With synchronize, I can combine both timetables with one time series and fill in missing data using linear interpolation. This results in a plot that shows my data over time without any missing data. To create the plot, I signed into ThingSpeak, selected Apps, and created a new MATLAB Visualization with my MATLAB code.

All ThingSpeak users are able to try this example or explore the other new MATLAB features directly on ThingSpeak. I will leave my temperature (163540) and humidity (163545) channels public, so you can try out timetable example without having to connect devices to ThingSpeak.

MATLAB Central is “a place where you can get answers.” We have over 100,000 community members and MathWorks employees all sharing projects and files, experience, and answering questions. And, ThingSpeak is showing up on MATLAB Answers and File Exchange. This is great news for the ThingSpeak Community. If you already have a MathWorks user account and use it on ThingSpeak, you already have access to MATLAB Central. All you have to do is sign in. If you are new to MathWorks, you can sign up for a free user account to gain access to MATLAB Central and other features of ThingSpeak.

Check out Ned Gulley’s post, “Going Way Back with MATLAB Central” to learn about how the MATLAB community has formed over the years.

Cheers to MATLAB Central hitting the 15th year mark! We are happy to be a part of the story.

The Top 10 Internet of Things Countries*

1. United States
2. India
3. Germany
4. United Kingdom
5. Italy
6. Brazil
7. France
8. Poland
9. Canada
10. Spain

*According to ThingSpeak Usage Stats

Loren explores the data using MATLAB Analysis and MATLAB Visualizations app built into ThingSpeak.

Offline Analysis: Analyzing Data stored on ThingSpeak

If you have desktop MATLAB, you can gain even more insights into our traffic data or any of your ThingSpeak Channels. You need to first import the data from ThingSpeak into desktop MATLAB. To simplify the retrieval of the data from ThingSpeak, we use the functions from the ThingSpeak Support Toolbox, available on MATLAB Central File Exchange.

readChannelID = 38629;
readAPIKey = '8NPXB8G515OAD94Q';

%% Read Data %%
[data, time] = thingSpeakRead(readChannelID,'DateRange',[datetime('Mar 13, 2016'),datetime('Mar 14, 2016')],'ReadKey', readAPIKey);

[via Loren on the Art of MATLAB]

We write the temperature and humidity values from the weather station to a ThingSpeak channel. At some point in the project, we started to wonder about dew point calculations. We wrote some MATLAB code that combined the temperature and humidity to calculate dew point. I did this using the ThingSpeak app, “MATLAB Analysis”. You can try this out with ThingSpeak now by signing in, selecting Apps, MATLAB Analysis, New, selecting “Calculate Dew point”, and clicking “Create”. This happens to be one of our built-in examples using our weather station’s public data.

It is great that it was easy to calculate dew point with MATLAB, but I want to see this analyzed data over time just like any other sensor data. The solution is a powerful combination of MATLAB Analysis and TimeControl. We use MATLAB Analysis to do the analysis and write the data to a ThingSpeak channel. Then, we use the TimeControl app to repeat the analysis every 5 minutes.

To setup MATLAB Analysis on a schedule, sign into ThingSpeak, select Apps, TimeControl, and New TimeControl.

My MATLAB code now runs every 5 minutes doing analysis and writing data to my ThingSpeak channel. The TimeControl settings can be tailored to your needs such as executing MATLAB code once a day or only on weekends. This combination of MATLAB Analysis + TimeControl allows you to create continuous analysis of your project data.

To try this out for yourself, we have a public channel of weather station data that we have collected in Natick, MA at our headquarters. You can use that data and do your own MATLAB Analysis and writing the results back to your own channel. Also, Check out the ThingSpeak Documentation where we have a complete tutorial for you to help get started with ThingSpeak and MATLAB.

On ThingSpeak, so far, the datetime function returned time set to UTC time zone by default. Starting at 10 am (EDT) on September 10^th 2015, the datetime function will return date and time set to your account time zone (at https://thingspeak.com/account). This will allow you to read data from your channel with timestamps zoned to your local time zone instead of UTC.

For example, my account time zone is set to Eastern Time (US & Canada), and when I ran the following MATLAB code at 12:23 pm, I received:

dt = datetime('now')
dt =
     10-Sep-2015 12:23:35

Prior to this change, I would have received:

dt =
     10-Sep-2015 16:23:35

As you can see, the timestamp is 4 hours ahead of my time zone, which was due to MATLAB returning time in UTC.

This change makes it easier for you to perform time related activities in your time zone. Note that this new feature is available for both thingSpeakRead and thingSpeakWrite functions as well. As an example, consider the following request to read data from the MathWorks Weather Channel:

MATLAB Code:

[data, timestamp] = thingSpeakRead(12397);
display(timestamp.TimeZone, 'TimeZone');

Output:

data =
     225.0000    3.8000   43.9000   95.8000
     0   29.9800    4.3000    0.0300
timestamp =
     10-Sep-2015 16:13:54
TimeZone =
     America/New_York

With this enhancement, you would no longer have to explicitly specify the time zone of your dates and time to read and write data in your time zone.

Here are a few other examples:

1. Read data corresponding to one entire day in your timezone:

startDateTime = datetime('September 10, 2015 00:00:00')
endDateTime = datetime('September 10, 2015 23:59:59')
readChannelID = 12397;
[data, timeStamps] = thingSpeakRead(readChannelID, 'DateRange', [startDateTime, endDateTime])

2. Read data between certain hours of a day (between 7 am and 9 pm):

startDateTime = datetime('September 10, 2015 07:00:00')
endDateTime = datetime('September 10, 2015 21:00:00')
readChannelID = 12397;
[data, timeStamps] = thingSpeakRead(readChannelID, 'DateRange', [startDateTime, endDateTime])

3. Generate a MATLAB plot in your local time zone:

[data, timeStamps] = thingSpeakRead(12397, 'Fields', 3, 'NumPoints', 10);
plot(timeStamps, data)

Note that, if at present, you are explicitly setting the time zone to your local time zone, you might see unexpected behavior in your code. Here are a few examples, based on support requests we have received:

1. If you are using datetime function in your code similar to the example below:

% Set the time now to variable dt
dt = datetime('now')
% Assign time zone to UTC since the dt is unzoned by default
dt.TimeZone = 'UTC';
% Convert the timestamp to ‘America/New_York’
dt.TimeZone = 'America/New_York'

To fix this, remove the “TimeZone” assignments since time is now returned in your time zone by default, and use the code below:

% Set the time now to variable dt
dt = datetime('now')

2. If you are setting the time zone of data returned by thingSpeakRead to your zone:

% Read data from a channel
[data, timeStamps] = thingSpeakRead(12397);
% Set the timezone to match your zone
timeStamps.TimeZone = 'America/New_York';

To fix this, remove the line with the “TimeZone” assignment, and use the code below:

% Read data from a channel
[data, timeStamps] = thingSpeakRead(12397);

For more information about the datetime function refer to the MATLAB documentation. If you need support, use the MATLAB section of the ThingSpeak Forum.

“We switched to SSD drives for all of our database servers,” said Lee Lawlor, Lead Engineer of ThingSpeak. “All of the upgrades are live and available to the entire ThingSpeak Community!”

The improvements decreased response time dramatically and improved large data set retrieval by ten times.

We keep hearing about how many Billions and Billions of things there will be connected. Just think about how much data that they will create! Yep, it’s Big Data, or even, Bigger Data. ThingSpeak is the only open data platform specifically designed for the Internet of Things available ‘in the cloud’ or on your own network to capture and distribute data from things.

A new homepage for ThingSpeak

When we look out into the Cosmos, we see Billions and Billions of stars and keep a fond memory of Carl Sagan in our hearts. As we connect this planet, we can’t but think of the scale and the magnitude that IoT will bring. Using this inspiration, we launched the new ThingSpeak.com!

Carl Sagan said, “We have lingered long enough on the shores of the cosmic ocean, we are ready at last to set sail for the stars.” We believe the same about the Internet of Things! Let’s get going!

Electric Imp is a connectivity platform for connecting Wi-Fi devices to cloud services, much like RealTime.io and Iota Wi-Fi modules and Spark.io. Some Electric Imp module’s come in an SD card form factor and adds Wi-Fi connectivity to what’s connected to the Electric Imp module. Access to the Electric Module happens via the Electric Imp cloud. While connectivity is simplified with the Electric Imp system, you will need a data service like ThingSpeak to complete the Internet of Things experience. Once data from Electric Imp devices are in ThingSpeak, you can easily build applications and interactivity with other devices and platforms.

We put together a quick start tutorial for the Electric Imp and ThingSpeak, so you can quickly and easily get the Electric Imp talking to ThingSpeak. The tutorial uses parts from SparkFun – the Electric Imp Wi-Fi SD module, breakout board, and USB cable / power supply.

Get started now…  Check out the official Electric Imp and ThingSpeak Tutorial and source code on GitHub.

All of the source code to connect Electric Imp to ThingSpeak and the 3D printer design files are available on Marcus’ blog ‘slickstreamer‘.

[slickstreamer / Dangerous Prototypes]

The Top 10 Internet of Things Countries*

1. United States
2. France
3. Poland
4. United Kingdom
5. Germany
6. Netherlands
7. Australia
8. Canada
9. Italy
10. Brazil 

*According to ThingSpeak Usage Stats

Question: How do I find ‘public’ ThingSpeak Channels?

In order to help developers find open data inside of ThingSpeak Channels, we created a new API for searching the public ThingSpeak Channels.

Here are the Public ThingSpeak Channels. We order the channels by activity and completeness. Channels may be tagged and this helps find data that you might find interesting for your application. We also have API commands that you can pass to the ThingSpeak Channel API to return the public ThingSpeak Channels in either JSON or XML format.

Here are some easy examples:

• http://api.thingspeak.com/channels/public.json – Returns the Public ThingSpeak Channels in JSON format
• http://api.thingspeak.com/channels/public.xml – – Returns the Public ThingSpeak Channels in XML format
• http://api.thingspeak.com/channels/public.json?tag=temperature – Returns the Public ThingSpeak Channels in JSON format that match the tag, “temperature”

For support and questions, please use the ThingSpeak Forum.

Indoor Environmental Quality (IEQ) is the measure of comfort and includes factors such as temperature, humidity, pressure, noise level, and indoor air quality. don’s original goal was to monitor the IEQ of his baby’s room, but he soon realized that his project has more applications around the house and for others.

Don published the full details of the project and submitted it to the Green Design Contest at Instructables. Great work!

[via Instructables]

The Supermechanical team put this combination of Twine and ThingSpeak to use right away. They created a “Productivity Quantification” system to capture events around the office and try to determine how productive they are. They were able to track how much coffee they were drinking, snacks they were eating, toilets they were flushing, and things they were finishing. The results are a quantified picture of office productivity and a beautiful display of the data via the ThingSpeak API.

Creating a Twine Action to push data to ThingSpeak is really easy to do. Here’s what it looks like…

To do more with ThingSpeak and Twine make sure to check out the tutorial on the Supermechnical blog.

[via Twine / SUPERMECHANICAL.BLOG]

We want to send a special thanks to powermik, oiotoshi, sekjal, and akinsgre for contributing new code and reporting bugs.

All of the latest code is available on GitHub, so start building your own Internet of Things today!

Duke says,

“A demo of how to use ThingSpeak (an IOT web site) with a Gadgeteer Gas Sensor Device. Data from the sensors are displayed in real time on ThingSpeak and using some of ThingSpeak’s cool features the Gas Sensor device can send out Tweets for Alert and Alarm conditions.”

Another awesome part of this project is that it uses .NET Micro Framework library, μPLibrary 1.8, created by [paolopat]. This library makes it really easy to tap into ThingSpeak web services by embedded devices. It’s great to see different parts of the project coming together from multiple ThingSpeak users. We appreciate the creative combinations and the efforts that you are putting into your projects. Thanks!

For more information, check out the live sensor readings on the project’s ThingSpeak Channel and download the complete source code at Codeshare.

[via >TinyCLR Forums]

Topics on the agenda:

• Switch over to Ruby on Rails 3.1
• ThingSpeak v2.0
• Active ThingSpeak Projects
• Adding modularity and tests to the GitHub repository
• …btw, we’re hiring!

Background on ThingSpeak:

ThingSpeak is an open source web application and API to manage devices, to create device interactions, and to store data. Users can use the hosted version of ThingSpeak or setup instances on their own servers by getting the source code from GitHub. The technology behind ThingSpeak is Ruby 1.9.2, Rails 3.0, EventMachine, Phusion Passenger, Nginx, and Memcached to form a highly scalable infrastructure for the emerging Internet of Things and its data model requirements.

You use ThingSpeak to Send and Receive “data” via simple HTTP requests, much like going to a web page and filling out a form. Data can be from
anything — Blood Sugar Levels measured by a glucose meter, Server Usage and Uptime reported by servers, or Location Info from a mobile phone. Once the data is in ThingSpeak, you can build applications that retrieve the data, use the data for process decision-making, and reporting.

[via Pittsburgh Ruby Users Group]

We have created a new ThingSpeak Sketch for Arduino 1.0 that you can use for the Arduino and Ethernet Shield or the Arduino Ethernet all-in-one. All you have to do is add your ThingSpeak Write API Key to the sketch, upload to the Arduino, and connect to your network. The sketch includes automatic network configuration with DHCP, domain name resolution using DNS, a watchdog / reset function to keep the Arduino online, and a function to update ThingSpeak Channels. The new sketch has been running without hiccup in our lab for few weeks. We hope that you get the same reliability. Go ahead and copy, transform, and combine…

View Arduino 1.0 –> ThingSpeak Sketch on GitHub

Here’s what ThingSpeak is in Brazilian Portuguese: ThingSpeak é um projeto de Internet Aberta das Coisas feito pela ioBridge!

Thank you much, Paulo or should we say, “Muito obrigado, Paulo?”

Behind the scenes, Lars uses the Arduino microcontroller to collect data from the sensors and uses Processing to publish data to his ThingSpeak Channel.

From Lars’ project site:

The goal of this project is to log some weather data and be able to access it from anywhere. There is some sensor data (temperature, relative humidity, pressure, and ambient light) and some computed data (dew point). You can see the weather condition in my apartment in Ithaca, NY at my ThingSpeak Channel 346. You can also look at the Google Chart of my own MySQL solution, which I no longer maintain.

Check out a detailed breakdown of the Weather Station project and more awesome projects on Lars’ project site, called “make.larsi.org“.