Installation

The Arduino IDE needs to have the ThingSpeak library installed in order for your devices to know how to send data to ThingSpeak. In the Arduino IDE, choose Sketch, Include Library, and Manage Libraries. Search for “thingspeak” and click Install.

Device Support

The ThingSpeak Communication Library supports many devices. Using the library makes the experience the same for each board type. When you learn one way to work with ThingSpeak, you will be to work with other devices in the same way.

• Arduino or compatible using a WiFi Shield
• Arduino or compatible using a WiFi Shield 101
• Arduino or compatible using an Ethernet Shield
• Arduino or compatible using a MKR ETH Shield
• Arduino MKR1000 (use the WiFi101 library version 0.13.0 or older. WiFi101 library versions 0.14.0 and newer have a bug that stops this ThingSpeak library from working properly)
• Arduino MKR1010
• Arduino VIDOR 4000
• Arduino GSM 14000
• Arduino Yún (Rev1 and Rev2)
• ESP8266 (tested with SparkFun ESP8266 Thing – Dev Board and NodeMCU 1.0 module)
• ESP32 (tested with SparkFun ESP32 Thing)

Each supported device includes three ThingSpeak examples.

• ReadField: Reading from a public channel and a private channel on ThingSpeak
• WriteSingleField: Writing a sensor value to a single field on ThingSpeak
• WriteMultipleFields: Writing sensor values to multiple fields and status in one transaction with ThingSpeak

Request Status Codes

To get the best compatibility with ThingSpeak IoT services, we recommend using the ThingSpeak library. The library has extra features that help you troubleshoot and get visibility into any issues with requests to ThingSpeak. I find it useful to store the last status code from ThingSpeak. I can use this code to understand if the request succeeded or failed. Here’s an example of how to use the “getLastReadStatus” method.

 // Read in field 1 of the private channel which is a counter  
 long fieldValue = ThingSpeak.readLongField(myChannelNumber, myFieldNumber, myThingSpeakReadAPIKey);  

  // Check the status of the read operation to see if it was successful
 statusCode = ThingSpeak.getLastReadStatus();
 if(statusCode == 200) {
   Serial.println("Field Value: " + String(fieldValue));
 }
 else {
   Serial.println("Problem reading channel. HTTP error code " + String(statusCode)); 
 }

The code behind the ThingSpeak library is available on GitHub. Discover other MathWorks Open Source and Community Projects on The MathWorks GitHub page.

I recently became the moderator of the MATLAB Maker Community that is hosted on MATLAB Central. There are many times where MATLAB and Simulink can help build a hardware-based project or be used to create the code running on a device. I also use MATLAB for analytics. Here are the most popular colors on CheerLights in the last 30 days.

The goal of the MATLAB Maker Community is to connect makers and builders together. I learn by working with others and sharing my work. If you are interested in maker project, I suggest following the Maker Community and jumping in on conversations or starting new discussions. I find this helpful if I am exploring a new idea or looking for feedback.

Right now, there is a discussion thread about how to use MATLAB to interface and interact with an Arduino. Makers can use MATLAB to control an Arduino by first installing the MATLAB^® Support Package for Arduino^®. Once you have the support package, you can use MATLAB to control the Arduino with familiar MATLAB commands.

% create an Arduino object
a = arduino('com3', 'uno');

% turn on an LED connected to Pin D11
writeDigitalPin(a, 'D11', 1);

% turn off an LED connected to Pin D11
writeDigitalPin(a, 'D11', 0);

Share your ideas on how to use the MATLAB connection to Arduino on the MATLAB Maker Community.

Setting up the Sensor

This project uses the ESP-based NodeMCU as an IoT gateway to forward sensor data to ThingSpeak. The NodeMCU is essentially a microcontroller and a Wi-Fi device that costs less than $10 US. The humidity sensor that is used in this project is the DHT11. This a very common sensor used to monitor temperature and humidity. The sensor either comes in a 4 pin or 3 pin package. The NodeMCU is programmed with the Arduino IDE using the code in Douglas’ tutorial or GitHub.

Using ThingSpeak Metadata

Douglas uses the metadata setting within a ThingSpeak channel to store condition ranges. This allows you to adjust settings in your online analytics code without redeploying new code. Each ThingSpeak channel has a metadata setting. You can store arbitrary text data that can be used in your MATLAB Analysis code. To load your channel’s metadata into MATLAB, use the webread function and add metadata=true to the ThingSpeak API Read Data request.

indoorChannelData = webread(strcat('https://api.thingspeak.com/channels/', ...
                                    num2str(indoorChannelID), ...
                                    '/feeds.json?metadata=true&api_key=', ...
                                    indoorChannelReadKey));

Using MATLAB for Condition Monitoring

Douglas uses MATLAB on ThingSpeak to determine the proper condition. This is a common requirement in complex IoT systems. This example could be a good starting point for building a condition monitoring system for industrial maintenance applications. You use MATLAB to determine the target humidity using a polynomial fit over the lookup data.

lookupFit = polyfit(humidityLookup(:, 1), humidityLookup(:, 2), length(humidityLookup) - 1);
optimalHumidity = polyval(lookupFit, curTempOut);

humidityDiff = curHumidity - optimalHumidity;

Using IFTTT for Alerts

Often you want to get notifications when a certain condition is met. Douglas shows you how to use IFTTT to send push notification directly to your phone. In this project, MATLAB is determining the condition and then interfaces with the IFTTT API to send the push notification. To send push notifications via IFTTT, use the webwrite function in MATLAB.

webwrite(strcat('https://maker.ifttt.com/trigger/', makerEvent, ...
                '/with/key/', makerKey), ...
                'value1', stateMsg, ...
                'value2', char(timeSinceChange, 'hh:mm'));

All of the MATLAB code can be deployed on ThingSpeak and scheduled to be executed periodically without having this on your desktop computer. The complete Smart Humidity Sensor project tutorial is available on Hackster.io. Feel free to discuss on the MATLAB Maker Community.

Naman uses an Arduino for processing the heartbeat data and turns the data into heartbeats per minute. Then, periodically, the device sends the data to ThingSpeak for data storage and data analysis using MATLAB. The heart rate monitor is connected to the internet using DFROBOT’s ESP8266 Wi-Fi Bee. The Wi-Fi Bee turns serial data-to-Wi-Fi.

This heart rate monitor sensor is a pulse sensor which is developed based on PPG techniques. This is a simple and low-cost optical technique that can be used to detect blood volume changing in the microvascular bed of tissues. It is relatively easy to detect the pulsatile component of the cardiac cycle according to this theory.

To build your own, check out Naman’s tutorial on either Hackaday or Hackster.

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

• ThingSpeak Documentation for Bulk-Update
• Continuously Collect Data and Bulk-Update a ThingSpeak Channel Using an Arduino MKR1000 Board or an ESP8266 Board
• Continuously Collect Data and Bulk-Update a ThingSpeak Channel Using a Particle Photon Board
• Continuously Collect Data and Bulk-Update a ThingSpeak Channel Using a Raspberry Pi Board
• MATLAB thingSpeakRead Documentation
• ThingSpeak Support Toolbox for MATLAB
• MATLAB Online

My process of smoking meat, cheese, or even ice cream is to monitor only the meat temperature and the internal temperature of the smoker. When I finish a cook, I go back and try to learn from the data. I do not attempt to control the smoker using the Internet of Things, I use IoT to collect the data with ThingSpeak, analyze the data with MATLAB, and apply the insights to the next cook. The best advice that I have been given is to not change too many variables. Stick with simple rubs, the same charcoal, the same wood, the same cuts of meat, etc. Only change one variable for one cook. It takes years of trial and error before you get great at BBQ.

With the help of ThingSpeak and MATLAB, I can help you understand one of the more frustrating parts of smoking meats… the stall! The stall is a period of time where what you are cooking does not seem to be increasing in internal temperature. I used to panic during the stall and mess with the temperature by adding more charcoal or turning the vents. Overtime, I realized this is normal. No reason to panic.

Cooking is taking something cold and getting its internal temperature up to a safe level. Everything that you cook has a different target internal temperature, but generally the sweet spot is 190-205F. Smoking is about low and slow cooking. This means that you are trying to raise that internal temperature slowly with a low temperature. I use a cook temperature of 230-250F. This means that smoking takes a lot of time to properly cook. In some cases, this is two hours per pound. Things don’t change much minute to minute in a BBQ pit, so you can collect data every few minutes and still have an accurate picture of what’s happening.

Collecting Data

First, I set up a ThingSpeak channel to store my temperature data. One field is for the smoker’s temperature and field two is for the internal temperature of what I am cooking. To get the data, you have many options. I did a quick search around the internet and discovered hundreds of Arduino and ThingSpeak projects to get data from a smoker. In general you need two temperature probes that can take the heat of the smoker, connectors, an Arduino with Wi-Fi like the MKR1000.

Analyzing the Temperature Data

The first step is to read in the temperature data using MATLAB that was collected by ThingSpeak. Data on ThingSpeak is stored in a channel and identified by a channelID. If you have a private channel, you will need to supply a Read API Key to get access to the data.

smokerTT = thingSpeakRead(279400,'ReadKey','9AYZQDT1XFDM98FW','OutputFormat','timetable','NumPoints',115);

Sometimes the data from your temperature probe is noisey. This means the value that the temperature probe reports is sometimes higher or lower than the actual temperature. If you take a few samples and take a median, you get a consistent result. In MATLAB, I use smoothdata to take a moving median of my time-series sensor data.

smoothSmoker = smoothdata(smokerTT);

After I clean up the data, I want to visualize it and to see what happened. This is a good time to learn how long things actually take, so on your next cook you budget the right amount of time and don’t rush any phases.

plot(smoothSmoker.Timestamps, smoothSmoker.Variables);

I can use this data to determine how long the total cook will last and even set alerts using ThingSpeak. I tend to watch the smoker and tend the fire.

Results

After a lot of research, I discovered what the stall is doing and why it is important to keep your patience and push forward. This is starting to sound like a metaphor for life. According to Prof. Greg Blonder, “The stall is evaporative cooling”. Prof. Greg is a physicist, entrepreneur, former Chief Technical Advisor at AT&T’s legendary Bell Labs, and regularly contributes to AmazingRibs.com. He likes to bust myths about barbequing and help us understand the thermodynamics of cooking. You are heating the meat slowly, but the moisuture in the meat is evapotaring at the same rate. This effect causes a stall in the temperature rise. The temperature of the meat will go up when the moisture is depleted. The stall is important to the cooking process and leads to something called the bark. This is an outer layer of the meat that is slightly thicker and less tender than the rest of the meat, but traps in lots of flavor and adds to its complexity. So, don’t rush during the stall. Keep the smoker temperature constant – avoid the temptation to turn the heat up to get through faster. And in the end, enjoy some well made BBQ with friends and family over the summer weekends and holidays.

MathWorks Arduino Resources

• Arduino Support from MATLAB
• Arduino Support from Simulink
• ThingSpeak Communication Library for Arduino

Maybe it’s time to build your version of a MATLAB and Arduino powered dartboard.

We hope you build some awesome projects using Arduino, MATLAB, Simulink, and ThingSpeak on Arduino Day!

Anders was determined to measure sound from over 20 demo stations at the same time and figure out who the the winner is. This turns out to be a complicated challenge and he used our tools such as MATLAB, Simulink, and ThingSpeak, to produce some interesting results. Here’s what the raw data looks like from just five sound sensor nodes at the demo stations.

The sensor nodes uses the Arduino Nano devices because they’re small, low-cost, and Simulink has an Arduino support package. Arduino Nano’s both low cost and energy efficient which is great, but it doesn’t have Wi-Fi. They connect the sensor nodes to an Internet-connected Raspberry Pi using an RF mesh network with the nRF24l01+ radio. The RF24 solution is both very cheap and energy efficient, which is valuable if you’re running them with battery power. Simulink Coder has a Raspberry Pi Support Package which simplified the workflow.

When you follow the tutorial, you are going to learn many things and experience their analytic workflow as they decide how to develop an algorithm to normalize sound levels, determine which data to send to ThingSpeak, and build visualizations to see the results of the project.

Anders also shared a library on File Exchange that allows users to communicate with RF24 chips on Raspberry Pi and Arduino boards. The library relies on the RF24Mesh library, and has S-functions that interact with the classes there. The File Exchange submission includes an example for the Arduino to read sensor data from a temperature sensor and sends it to the gateway Raspberry Pi and then sends the data to ThingSpeak. In order to download the File Exchange, you need to sign in with your MathWorks account. This would be the same account that you use on ThingSpeak.com.

Visit ThingSpeak Tutorials, to see the complete tutorial for Building a Dynamic and Self-organizing Network of Devices.

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.

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

[via ThingSpeak Tutorials]

You only need a few things to build a light and temperature sensor that writes data to ThingSpeak:

• Arduino Zero or Uno Board
• Arduino Wifi Sheild 101
• Photocell
• Temperature Sensor (This example uses a TMP36)
• 10K Ohm Resistor

Once you have the circuit built, you create a ThingSpeak channel, connect the Arduino WiFi 1010 to your Wi-Fi network, and install the source code from the tutorial on the Arduino.

Data is now being sent to your ThingSpeak Channel. Go to your channel to see two charts of the light and temperature data. To take the project a step further, go to ThingSpeak Apps and use MATLAB to analyze and visualize and trigger actions from the data.

[via Arduino.cc]

Arduino IDE Installation

In the Arduino IDE, choose Sketch/Include Library/Manage Libraries. Click the ThingSpeak Library from the list, and click the Install button.

Particle / Spark IDE Installation

In the Particle/ Spark Web IDE, click the libraries tab, find ThingSpeak, and choose “Include in App”.

Compatible Hardware

• Arduino or compatible using an Ethernet or Wi-Fi shield (we have tested with Uno and Mega)
• Arduino Yun running OpenWRT-Yun Release 1.5.3 (November 13th, 2014) or later.
• Particle Core or Photon (Formally Spark)

ThingSpeak Examples

The library includes several examples to help you get started.

• CheerLights: Reads the latest CheerLights color on ThingSpeak, and sets an RGB LED.
• ReadLastTemperature: Reads the latest temperature from the public MathWorks weather station in Natick, MA on ThingSpeak.
• ReadPrivateChannel: Reads the latest voltage value from a private channel on ThingSpeak.
• ReadWeatherStation: Reads the latest weather data from the public MathWorks weather station in Natick, MA on ThingSpeak.
• WriteMultipleVoltages: Reads analog voltages from pins 0-7 and writes them to the 8 fields of a channel on ThingSpeak.
• WriteVoltage: Reads an analog voltage from pin 0, converts to a voltage, and writes it to a channel on ThingSpeak.

Complete open source code and examples for the ThingSpeak Library are available on GitHub. Discover other MathWorks Open Source and Community Projects on GitHub.

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!

The sensor records the PM10 and PM2.5 dust levels to get an accurate indication of the dust in the air. This project is a great example of how a little sensor could turn into something important for protecting machine shops, construction sites, and garages.

[via shadowandy / GitHub]

RunnerHam Tweets his distance and time when he takes a run on his wheel, “I’m done! 57.62m at 0.61m/s”. You can also check out his ThingSpeak Channel where he records lots of data about his day.

Ángel also released an Instructables explaining his “pet project” so you can make your own and make your own enhancements. Just imagine what you can do with some sensors, connectivity, and ThingSpeak Web Services!

[via Instructables]

Blynk is an Android / iOS app that allows for a 5 minute, out-of-the-box experience for Internet of Things projects. Blynk already supports Arduino, Raspberry Pi, and in the future Electric Imp, Spark, The Airboard, Wildfire by Wicked Device, Tiny Duino, and ESP8266 Wi-Fi.

ThingSpeak offers the Internet of Things stable data storage, fast retrieval, data processing, data visualizations, and hooks to every web service possible. We are thrilled that Blynk is planning to support the open APIs of ThingSpeak to extend any IoT project with ThingSpeak web services.

The Blynk Kickstarter campaign ends at 12pm EST on February 14th. You have less than 48 hours to support Blynk! $20+ pledges will also get free 1 year premium account at Codebender.

[via Kickstarter]

The idea is that it is frustrating waiting for luggage at the airport and wondering where it is and why it is not on the baggage carousel. With this project, you can track luggage from start to finish. The advantages are not only for the traveler, the airlines could track luggage as well and get quality statistics for each airport. And, the base system has many applications outside of travel such as the Automotive Industry.

Chris explains the project really well on his blog and with a YouTube video.

For more information check out the FastLED and Arduino tutorial and the Arduino Sketch on GitHub.

Mi Humidor de Cigarros conectado a Internet por medio de un Arduino

We have developed a new ThingSpeak App and it is available now to all ThingSpeak Users.

The new TalkBack App allows devices to check ThingSpeak for commands to execute. TalkBack is perfect for battery-powered devices that need to sleep most of the time and wake up to see if there is anything to do and then go back to sleep, like a door lock for example. The lock is mostly going to be asleep to save battery power, but it can wake up periodically and check TalkBack or be woken up by a button press to see if it should be opened or not.

Devices powered by ThingSpeak and now with TalkBack will be able to both push sensor data to the ThingSpeak Cloud and check TalkBack if any commands are available all in one request. To get started, we have the complete TalkBack API Documentation and an Arduino Yún Tutorial available now.

Atmel-powered Arduino Yún Tutorial

With the release of TalkBack, we created a tutorial for the Arduino Yún. The “Yún” is a special combination of easy-to-program Arduino with an additional processor, an Atheros AR9331, running Linux and the OpenWrt wireless stack. Programming the Arduino via USB is identical to the Arduino Leonardo. Once the Arduino Yún is connected to Wi-Fi, the Arduino has full access to ThingSpeak Cloud Services and the TalkBack App and API. Check out the Controlling the Arduino Yún with TalkBack tutorial for a step-by-step way of controlling the Arduino Yún via TalkBack and the ThingSpeak Cloud.

TalkBack is available now to all ThingSpeak Users and to new users by Sign Up for Free at ThingSpeak.com! Please feel free to share with us and the ThingSpeak Community with the awesome ways you use TalkBack with your ThingSpeak Projects!

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]

[via Facebook]

The technology behind Tweet-a-Tweat is Arduino + ThingSpeak — this is another powerful combination. The Gumball Machine is from Beaver Vending and has an Arduino inside listening to the TweetControl App from ThingSpeak. TweetControl listens to the Twitter stream for keywords that trigger HTTP requests in real-time. The heavy lifting happens in the cloud so that the embedded Arduino only has to focus on moving servos and being ready for web requests.

For more information, visit Tweet-a-Tweat and check out the live video feed of Philter’s Twitter powered gumball machine being operated live.

[via Tweet-a-Tweat]

Here’s what the temperature looks like now in Australia:

Check out the family’s blog for the source code and to learn how to create your own solar water heater monitoring system.

[via Klink Family Adventures]

This video that we discovered on YouTube is the team’s presentation. You will get to see ThingSpeak in action, live in front of an audience about halfway thru…

We hope you got an “A” on the project (do they still give letter grades?)!

Since the project release, there has been much activity. A part from CheerLights being discussed on blogs like MAKE and Lifehacker, the community has created some interesting bits of tech that extend the project further than lights. So if you don’t have a way to connect your lights together with CheerLights, you can connect your mobile phone, browser, and web sites together by subscribing to the CheerLights feed. Right now you can check the latest CheerLights color with an Android App created by @ChrisLeitner. Another really neat thing is a browser plugin for Chrome designed by Josh Crumley. So, in the top corner of your web browser you can see the latest color in an unassuming way. It’s a little reminder that we are connected.

To join CheerLights, all you have to do is build something that subscribed to the CheerLights ThingSpeak Channel or access the data using JSON and XML. You can also use the apps, browser plugins, or web widgets to see the colors. Visit the CheerLights website hosted on Tumblr for details on making a controller with Arduino, ioBridge, or Digi’s ConnectPort.

To control CheerLights, just send a Tweet to @CheerLights and mention a color.

Just think when you send this Tweet that you are updating 1000’s of lights, apps, browsers, and widgets all at the same time.

Spread some cheer…

[via MAKE / Lifehacker / CBC / ioBridge Projects]

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

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“.

willnue added the ability to tweet to his GE Wireless Control Center Alarm system. He added an Arduino with Ethernet Shield and uses the ThingTweet app to connect the alarm to Twitter. Check out his detailed Instructables to learn more, build your own social thing, and enter the contest.

wilnue says,

This project will add tweeting capabilities to the GE 45142 Choice-Alert Wireless Control Center Alarm system. The alarm system allows you to connect up to 16 different sensors across 4 zones and with the addition of the Arduino powered AlarmingTweet you can enable it to keep you informed of its status anytime anywhere.

Good luck with the contest!

[via NueWire / Arduino Forum]

Paul says,

I wanted to know how much time I was spending under the shower each day, especially in these environmentally conscious times. The benefits of that are that I can perhaps save some money on the water bills and also study the effect of temperature on my showering time.

[via Paul Asselin]