raspberry pi – Internet of Things

Send Bulk Sensor Data to ThingSpeak for Analysis

Hans Scharler — Thu, 20 Jul 2017 15:00:17 +0000

Many IoT projects collect data from a sensor and send the data to ThingSpeak at the same time over and over. To continuously collect and send data to the cloud requires the device to be powered and connected all of the time. A battery-powered IoT device like a Particle Photon or Onion Omega2 would run out of power quickly. There are many IoT applications where you want your IoT device to collect the data offline over a long period of time, then send the data all at once to ThingSpeak for analysis.

The ThingSpeak team at MathWorks is excited to announce Bulk-Update! This new ThingSpeak feature is targeted at IoT devices trying to optimize battery use by allowing the device to update a lot of data at once. To help you get started with bulk-update, we have written examples for Arduino, ESP8266, Particle Photon, and the Raspberry Pi 3.

Once your data is on ThingSpeak, it is easy to analyze using the MATLAB Analysis and Visualization apps within ThingSpeak, MATLAB Online, or Desktop MATLAB. To read data from ThingSpeak into MATLAB, use the ThingSpeak Support Toolbox and the thingSpeakRead command. We have released documentation and examples to help you get started with bulk-update on ThingSpeak.

Resources for Bulk-Update

Counting Cars and Analyzing Traffic

Hans Scharler — Fri, 18 Sep 2015 21:05:59 +0000

The power of any tool becomes magnified when you start combing it with other tools. In this File Exchange project by Eric Wetjen, he demonstrates a powerful project by using a webcam to gather live traffic video of Route 9 in Natick, MA, using Simulink to deploy a car-counting algorithm to a Raspberry Pi, using MATLAB to perform analysis, and using ThingSpeak to collect and share the analyzed data with others.

The project uses a Raspberry Pi 2 and USB webcam acting as a sensor. The webcam picks up traffic flowing in both directions. Once the algorithm for detecting cars is modeled in Simulink, the algorithm gets deployed on the Raspberry Pi. The Raspberry Pi sends the raw data to ThingSpeak on regular basis where it is analyzed using the MATLAB Analysis app on ThingSpeak.

After sending to ThingSpeak, Eric created a MATLAB Analysis app to calculate the daily traffic-volume on ThingSpeak Channel 51671. Now that the data is public, others could use this processed data within apps such as Waze to optimize directions using analyzed traffic flows.

Check out the article for the complete project details and all of the code to get your Raspberry Pi + ThingSpeak analysis project started.

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

Hans Scharler — Thu, 20 Aug 2015 19:27:30 +0000

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!

Store, Share, and Visualize Sensor Data using the BrickPi, Raspberry Pi, and ThingSpeak

Hans Scharler — Fri, 15 Nov 2013 18:05:29 +0000

Dexter Industries launched a very successful Kickstarter campaign this past summer to build and release the BrickPi. The BrickPi turns the Raspberry Pi computer into a robotics and sensing platform for LEGO^® MINDSTORMS^®. Since the wrap up of the campaign, users have jumped on board making cool projects using the BrickPi including a step-by-step tutorial using ThingSpeak to store, share, and visualize sensor data.

Check out the tutorial, “ThingSpeak Temperature with Raspberry Pi“, to learn how to send sensor data using the BrickPi, a Raspberry Pi computer, and a temperature sensor for the LEGO^® MINDSTORMS^® NXT. The project uses ThingSpeak to store, share, and visualize sensor data collected by BrickPi-enabled projects. The Python code for the Raspberry Pi is available on GitHub and the entire project is open source!

[via Dexter Industries]

EVE Alpha – Raspberry Pi Wireless Development

Hans Scharler — Sat, 17 Nov 2012 00:27:57 +0000

Kickstarter over the past few months has been the platform of choice for new Internet of Things hardware being developed. Many projects are an Arduino and another thing attached to it. While some of those projects are cool, they are not pushing the Internet of Things forward. Recently, Kickstarter changed their policies about hardware projects and also opened up the platform to the United Kingdom. This is forcing the projecteers to come up with more developed and innovative ideas that help differentiate themselves from rehashed projects and ideas.

One that has piqued our interest is the EVE Alpha for the Raspberry Pi created by Ciseco from Nottingham, United Kingdom. Wireless is a key part of the Internet of Things as with wireless we can connect more things in a more seamless way, then bridge them to the Internet. EVE Alpha aims at giving you a lot of wireless options in a tiny form factor all connected to an integrated computer called the Raspberry Pi.

Members of the ThingSpeak team are backers of this project and many others. We love finding new ways to get data to and from web services. This is exactly what we are here to do! We are looking forward to connecting the EVE to a host of web services (and ones we haven’t even released yet). Another key feature is the suite of wireless technologies that we want to prototype with all on one board. At the timing of this writing the EVE Alpha Kickstarter campaign is close to being funded, so there are high chances that Ciseco will deliver the Swiss Army knife of wireless development platforms!

[via Kickstarter]