The tide height is calculated using an ultrasonic level sensor. This measurement is taken periodically and then sent to ThingSpeak, an IoT analytics cloud platform by MathWorks, using a cellular modem. The system can easily be adapted to collect data about any environmental system such as greenhouses or oyster farms.

Once you have the data in a ThingSpeak channel, you use MATLAB to preprocess and clean up the data. The raw data some times has extraneous values caused by environmental factors such as lighting, cabling, and electrical interference. Sometimes, you have missing data caused by connectivity issues. It is important to clean up the data before you use the data in your analysis.

To predict future tide levels and send alerts when the tide is rising or falling, we use the MATLAB Analysis app on ThingSpeak. With MATLAB, we can use historical data to make a prediction about the future tide levels. This predicted tide level can be used to help schedule a boating trip or plan for a water surge after a storm.

Tide Alerts

Remembering to check the tide level when fishing or lazing on the beach is not particularly convenient. A much more useful approach is to have the system send a message when the time has come to pack up and start heading back to the dock. The timing of the alert depends on how much water depth is needed by a particular boat. Larger boats need higher water levels in order to move without getting stuck in the mud. One way to send alerts is to use ThingSpeak and MATLAB to detect changes in tidal height and send alerts.

Conclusion

Developing a tide monitoring system provided accurate tide level measurement and tide level prediction, with the added ability to send alerts. Robert has been able to avoid being stuck in the bay by providing enough time to get back to his dock using this system. This project also serves as a useful approach to solving many data-driven puzzles by having a reliable way to collect, analyze, and act on data. Using MATLAB, the accuracy of the tide levels improved by understanding the proper tide levels at a specific location and when the tide levels will change. If you used the general tide forecast, you would have to account for several inches of tide height difference.

Resources

• Developing an IoT Analytics System with MATLAB, Machine Learning, and ThingSpeak – MathWorks Technical Article by Robert Mawrey
• Measure and Analyze Tide Levels with ThingSpeak and MATLAB – Hackster tutorial
• TideAlerts.com – Robert’s website dedicated to the exploration of tides

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.

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.

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”.

Example MATLAB Visualization Code

lights = thingSpeakRead(1417,'OutputFormat','table','NumDays',30);
hist(categorical(lights.LastCheerLightsCommand))
set(gca,'XTickLabelRotation',45)

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!

Hackaday.com wrote an article about Vegard’s soldering iron connected to the Internet of Things. Here’s what they had to say:

The data pushes out to the ThingSpeak server which handles pushing data out to the bigger network, and data representation (like the cool Google gauge…). The best part: [Vegard] gets a phone notification when he accidentally leaves his soldering iron on. How perfect is that?

That looks a lot like our desks… wires, microcontrollers, pliers, cutters, Wi-Fi modules, and soldering irons. And now, the soldering iron is on the Internet of Things.

[via Vegard Paulsen / Hackaday.com]

[via Twitter]

Greg built the project out of necessity to help his plants suffering from “localized drought”. Let’s hope his plants get proper watering and that other ThingSpeak users can quickly and easily build this project. Thanks for sharing!

[via Instructables]

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

As more and more users create TweetControls, the service started slowing down. We have enhanced how the service works and now you get instant TweetControls!

In an Instragram video sending a Tweet and changing the CheerLights color, you will see that there is little delay between sending the Tweet and executing the control command to change the colors on his Christmas tree.

Learn more about TweetControl on ThingSpeak Docs.

The first step is to link a Twitter account to ThingSpeak.

Next, we’ll create a new TimeControl with the following values:

• Name: “CheerLights to Twitter”
• Frequency: “Recurring”
• Days: “Mon”, “Tue”, “Wed”, “Thu”, “Fri”
• Time: “9:40 am”
• Fuzzy Time: “+/- 10 minutes”
• Action: “ThingTweet”
• Tweet: “It is currently %%datetime%% and CheerLights is %%channel_1417_field_1%%.”
• Twitter Account: (select your linked Twitter account)

Save this TimeControl and you’re finished.  Every weekday within 10 minutes of 9:40 am in your timezone, TimeControl will send a Tweet with the current datetime and the current CheerLights color.

The CheerLights Channel ID is 1417, and colors are saved in field 1, so %%channel_1417_field_1%% will be replaced with the current CheerLights color.  You can change these values to access the most recent data from your own Channels.

Here’s an example Tweet from this tutorial.

It has been a real treat watching this project evolve as more and more people add lights… and other things. Things like Android and iPhone apps that check the latest color of CheerLights, Christmas trees, and robots.

To control the lights around the world, send a Tweet mentioning @CheerLights and a color. The command is processed by the ThingSpeak IoT analytics platform and distributed to all of the lights listening to the CheerLights API.

@CheerLights I am dreaming of a White Christmas

Internet of Things

Another powerful aspect of the CheerLights project is that is shows off what is possible with the emerging Internet of Things. With a single message sent via a social network like Twitter, 1000′s of objects around the world are in sync with each other. Lights are connected by many types of controllers, such as Arduino, ioBridge, Philips, and the Raspberry Pi. This project is only possible through the Internet and the coordination of developers around the world.

In the article, “How the Internet of Things Will Change Our Lives“, CheerLights is included to indicate how we are connected and how objects may bring people closer.

Learn how to join the project at CheerLights.com.

We are all connected…

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]

[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]

Download the free Application Note, “Interfacing Flyport to ThingSpeak”, and the Source Code to get your Flyport connected to web services via ThingSpeak.

https://blogs.mathworks.com/iot/documentation/apps/tweetcontrol/

TweetControl allows you to monitor Twitter for trigger words to send ThingHTTP requests. The CheerLights project by ioBridge Labs uses TweetControl to update its ThingSpeak Channel so other lights around the world stay in sync with each other.

Why use TweetControl? Our app connects to the Twitter Streaming API. What this means to you is that you don’t have to keep polling Twitter for status updates. You can sit back and let TweetControl listen and then process the request when a trigger word gets fired. This happens in real-time and it’s quite remarkable to see in action.

TweetControl is a part of our collection of apps for social things.

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!

Imagine an “Easy Button” for Twitter. All you have to is Tweet a hashtag from your Twitter account to control anything that has a web service API.

The applications for TweetControl are endless, and we are excited to see what you come up with. Check out the documentation for TweetControl to help you get started.

With this project, I wanted to take it a few steps further and build something from the ground up that’s focused on collecting enormous amounts of data from everyday objects, allowing devices to interact with each other, and building applications to present some meaning.

[via I am ShadowLord Blog]