25
Jul 16

Analyzing Squirrel Behaviour and Weather Forecasting with MATLAB and ThingSpeak

Lord Kelvin said, “If you can not measure it, you can not improve it.” In Carsten’s project, he built a squirrel feeder complete with sensors and a camera. The “Squirrel Cafe” allows squirrels to lift a cover and take a peanut. When that happens, data gets collected and the feeder tweets its data summary with a photo. Carsten is learning a lot about the behaviours of the squirrels and is also trying to forecast the coming winter based on how many nuts are being taken. Behind-the-scenes, he is using Raspberry Pi, ThingSpeak, and MATLAB.

Squirrel Monitoring

The Squirrel Cafe is connected to the ThingSpeak IoT Analytics platform using the Raspberry Pi. The Raspberry Pi collects data from a tilt sensor, temperature sensor, and a camera to determine how many nuts the squirrels are taking. Whenever the lid opens, the current temperature gets measured by the DS18B20 sensor and sent to ThingSpeak for storage and analysis using MATLAB.

Squirrel Cafe System

Carsten is also testing a theory. He noticed through observation that there might be a correlation between the number of nuts that get taken from the feeder and how long the coming winter season will be. This winter forecast and “nuts per minute” calculations are being performed by ThingSpeak’s MATLAB Analysis app. We are excited to see what the results prove in the next few years.

For full project details and source code, visit Carsten’s website for this project at www.TheSquirrelCafe.com.

 



09
Jul 16

Prototyping IoT Analytics with MATLAB and ThingSpeak

Rob Purser, our Senior Development Manager for IoT, will be holding a hands-on workshop at this year’s IoT Evolution in Las Vegas. Rob will teach the attendees how to prototype IoT analytics using MATLAB and the IoT platform, ThingSpeak.

IoT Evolution - Internet of Things Conference

The Internet of Things typically involves a discussion of smart devices and the cloud, with much less attention paid to the data collection, pre-processing of acquired data, and development of real-time analytics algorithms. A successful data analytics strategy involves embedded sensor analytics, historical data analysis, and online analytics. In this hands-on session, each participant will work with devices and try out the various types of analytics in action.

IoT Evolution West 2016

Caesars Palace, Las Vegas
900 Convention Center Blvd
New Orleans, LA

IOTD-02: Prototyping IoT Analytics: Hands on with ThingSpeak and MATLAB
Tuesday, July 12, 2016 at 2PM
Forum 15



24
Jun 16

What Do Students Need to Learn to Be Successful in IoT?

I will be joining a panel at the ASEE’s 123rd Annual Conference in New Orleans. The goal of our panel is to discuss what students need to learn to be successful in IoT. Our session is Tuesday, June 28th, 2016 at 1:15pm in Room 261 at the New Orleans Convention Center.

ASEE IoT Conference 2016

The IoT panel at ASEE will be moderated by Dr. Gerald W. Recktenwald and features Dr. Jacob Segil from the University of Colorado, Boulder, Dr. Duncan James Bremner P.E. from the University of Glasgow, and Hans Scharler from MathWorks.

American Society for Engineering Education Conference

New Orleans Convention Center
900 Convention Center Blvd
New Orleans, LA

T426·IoT: What Do Students Need to Learn to Be Successful in this Field?
Tuesday,  June 28, 2016 1:15 PM to 2:45 PM

 



06
Jun 16

Weather Station with Particle, SparkFun, ThingSpeak, and MATLAB

[Haodong Liang] has released a weather station project with full MATLAB data analysis, device source code, and procedures on Hackster.io. He used the Particle Electron to connect the SparkFun weather station to ThingSpeak anywhere covered by a 2G/3G cellular data network. The project demonstrates how to build your own and start exploring data collected by ThingSpeak with MATLAB.

MathWorks Weather Station

The project also shows you how to use MATLAB to get very detailed visualizations and data analysis of the data collected by the weather station. Some of the examples include histograms of temperature, humidity, and pressure, curve fitting, daily comparisons, and 3D plots of temperature.

MATLAB weather station temperature plot

Visit Hackster.io for the complete tutorial to build your own weather station, connect it to the internet with the Particle Photon, collect your data with ThingSpeak, and do data analysis with MATLAB.

[via Hackster.io]



27
May 16

IoT Quick Start With the Arduino MKR1000 and ThingSpeak

If you are looking to start with the Internet of Things, then try out the Arduino MKR1000 and connect it to the ThingSpeak IoT Platform. We have put together a complete tutorial that uses the MKR1000 to collect data about your Wi-Fi signal and send it to ThingSpeak for storage, analysis, and visualization.

Arduino MKR1000

The Arduino MKR1000 is a great starting point when learning about the “things” in IoT. The MKR1000 has a microcontroller, Wi-Fi module, encryption module, and a battery-charging circuit. It’s easy to get started and once you get it connected to ThingSpeak, you have a lot of “cloud power”. ThingSpeak has a suite of apps to allow the Arduino to post messages to Twitter, do data analysis, show charts and visualizations, and be controlled by schedules and external events. With these building blocks you can prototype any IoT system.

ThingSpeak Channel Data

Once you have your data on ThingSpeak, you can analyze and visualize the data with built-in MATLAB apps.

[via ThingSpeak Tutorials]



21
Apr 16

ThingView – Mobile App to See ThingSpeak Charts on Android Devices

Cinetica has released to Google Play, a new app to see ThingSpeak charts on Android smartphones and tablets. The app is called ThingView and has already reached 5,000 installs on Android devices!

ThingView Android App for ThingSpeak Charts

Even if you do not have devices and sensors sending data to ThingSpeak, you can still use ThingView to see public channels. For example, if you want to see the charts created by sensors in my house, just add Channel ID 9 to ThingView. You see charts of light levels and temperature generated by my house.

Check out ThingView on Google Play!



31
Mar 16

ThingSpeak is a New Hackster Platform for Sharing Projects

Hackster.io announced that ThingSpeak is now a platform on their project sharing website!

Hackster Platforms

The ThingSpeak platform joins the likes of Amazon Echo, ESP8266 Wi-Fi, and Particle.io platform. ThingSpeak users can easily document, share, and reproduce hardware and Internet of Things projects using Hackster.io. We are already off to a great start with 13 documented projects and tutorials and 31 community members. Check out our platform on Hackster.io to discover great projects and build your own IoT projects.



25
Mar 16

Explore your IoT data with ThingSpeak and MATLAB

Loren Shure, a blogger at MATLAB Central, has written a new blog post about Eric Wetjen’s Counting Cars and Analyzing Traffic project. Eric uses a Raspberry Pi and webcam to capture traffic data outside of the MathWorks headquarters in Natick, MA. All of the traffic data is stored on a public ThingSpeak channel, so you will be able to use it to learn data analysis with the built-in MATLAB Analysis and Visualizations apps in ThingSpeak. Continue reading →



11
Mar 16

New MATLAB Analysis Feature – movmax – for ThingSpeak

My power meter at my house reports its power every few minutes. I capture that data and send it to ThingSpeak. The value reported is the total kilowatt-hour (kWh). I would love to see the maximum value over an hour versus randomly reported values over an hour. With the release of MATLAB R2016a, ThingSpeak users have access to a new suite of data analysis features. One of them is movmax – with movmax, I now can look at my ThingSpeak data over a time and figure a moving window of maximum values. This new feature is highly customizable for your application, but I will show you how I use it.

My data over an hour looks like this: 803, 919, 724, 1349, 1500, 602, 549, 899, 1678, 1577

Using movmax, I can have a sliding window ran over my data to pull out a maximum value from the window and use it for a visualization or further analysis.

The MATLAB code to process my power data is really straightforward.

readChannelID = 97871;
fieldID1 = 1;
readAPIKey = '7MOXB8G515OAD94Q';

%% Read Data %%
[data, time] = thingSpeakRead(readChannelID, 'Field', fieldID1, 'NumPoints', 10, 'ReadKey', readAPIKey);

%% Process Data %%
data_max = movmax(data, 4)

%% Visualize Data %%
thingSpeakPlot(time, data_max);

Now, using the MATLAB Visualizations app on ThingSpeak, I can visualize the data. Here’s the before and after.

Power Data Processed Data with MATLAB movmax

You can use movmax in the MATLAB Analysis or MATLAB Visualizations apps on ThingSpeak. Sign up or sign into ThingSpeak, select Apps, and click “MATLAB Visualizations”. Create a new one with the blank template and use my MATLAB code. I will leave my channel of data up for you to try out. You can use channel number 97871 and my read API key 7MOXB8G515OAD94Q. The power data is stored in field1.



08
Mar 16

Getting Started with IoT using the Particle Electron and ThingSpeak

Julien Vanier over at Hackster.io created a new tutorial showing you how to get started with the Internet of Things using the new Particle Electron and ThingSpeak.

Particle Electron Kit using ThingSpeak IoT

The Electron is a new 3G connected IoT device using cellular data and works anywhere you can get 3G in the United States. It is really awesome to plug-in a device and get it connected without the issues of Wi-Fi. This development kit also makes it possible to build battery-powered, mobile sensors. Good thing that ThingSpeak supports GPS data and offers sensor data analytics.

Check out Julien’s tutorial to go “From 0 to IoT in 15 Minutes” and other ThingSpeak projects on Hackster.io.