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

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.

Allie uses the MATLAB Analysis app on ThingSpeak to check her to do list and see if anything is overdue. If a task is overdue, the MATLAB code writes the task overdue into a ThingSpeak channel. The MATLAB code is very straightforward and does a bit of analysis on her task list to see what is overdue. To get the MATLAB Analysis code to keep checking her task last, she schedules the MATLAB code using the TimeControl app on ThingSpeak.

Allie also has other ideas on how to make use of her status light:

• Alert you when you’ve forgotten to water your plants
• Tell you when you’re out or range of important objects like your keys or wallet
• Combine with IFTTT to alert you when you’ve forgotten to respond to emails or phone notifications

To build your own Remembrall light, follow the step-by-step tutorial on Instructables.

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]

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.

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.

By following our tutorial, you will be able to use ThingSpeak to send messages to your team’s Slack channel. This will also allow devices like an Arduino to use Slack since ThingSpeak will take care of authentication and HTTPS.

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.

Electric Imp is a connectivity platform for connecting Wi-Fi devices to cloud services, much like RealTime.io and Iota Wi-Fi modules and Spark.io. Some Electric Imp module’s come in an SD card form factor and adds Wi-Fi connectivity to what’s connected to the Electric Imp module. Access to the Electric Module happens via the Electric Imp cloud. While connectivity is simplified with the Electric Imp system, you will need a data service like ThingSpeak to complete the Internet of Things experience. Once data from Electric Imp devices are in ThingSpeak, you can easily build applications and interactivity with other devices and platforms.

We put together a quick start tutorial for the Electric Imp and ThingSpeak, so you can quickly and easily get the Electric Imp talking to ThingSpeak. The tutorial uses parts from SparkFun – the Electric Imp Wi-Fi SD module, breakout board, and USB cable / power supply.

Get started now…  Check out the official Electric Imp and ThingSpeak Tutorial and source code on GitHub.

Merci beaucoup.

[via YouTube]

We are starting a video tutorial series, so you can see how to get started with ThingSpeak right away. The first two videos are available now along with our 20 other tutorials for ThingSpeak. Check out the Tutorials section of the ThingSpeak Community website.

Introduction to the “Internet of Things” and ThingSpeak

ThingSpeak Channels