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

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]

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]

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.

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

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]

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

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!