Do you want to implement Internet of Things specific applications? Then this article is about Internet of Things Implementation using ThingSpeak with MATLAB.
Internet of Things is a technology wherein the devices gets connected to internet. The connected devices likewise communicate either among each other or with the people. Finally they provide the sensed data to the cloud. The data can bring out an insight to the data. Therefore, the smart connected devices find applications in health monitoring, home automation, predictive analysis, industrial monitoring to name a few.
The smart devices are connected to the data aggregator i.e., the cloud. Furthermore to know more about Internet of things topologies refer the link below.
The data aggregators makes use of the software platform like MATLAB to perform analysis and visualization of the data. First of all getting data had been a big difficulty those days, but now we are overwhelmed with data and many researches are being carried out to bring out an insight in those data. To get data, a simple device which includes a sensor, controller and transmitter is sufficient. Then, a data aggregator and a software platform are required to examine more on the data. Gone are those days where the people found it difficult to get data from device via internet. Now the biggest task is to identify and find a solution with the numerous amounts of data which is available. The most noteworthy platform which does the work is the ThingSpeak.
ThingSpeak had been launched in the year 2010. Hence now interaction with the devices, web services and social media is possible with ThingSpeak. It is a platform for Internet of Things that lets the user collect the data and store it in cloud and develop applications in any IoT platform. Thus the ThingSpeak acts like a data collector. The sensed value sending nodes is called the edge devices. The edge devices send value to the data collector. The ThingSpeak can study the historical data and comprehend the data. The ThingSpeak link is given below.
- Sensor: Any sensor data.
- Controller: Arduino, Raspberry Pi, BeagleBone Black etc .The controllers should support TCP/IP, HTTP or MQTT.
- Visualization of data : MATLAB.
- Location Tracking Application.
- Thermostat Control.
- Energy Data Analysis.
- Tide Prediction.
- Weather Station.
- Design a custom IoT analytics environment and algorithms.
- Create digital twins by physical driven models..
- To prototype small scale systems.
Features of ThingSpeak:
- Data gets collected in private channels.
- Data is shared in public channels if required.
- REST and MQTT API is supported.
- Supports numerous micro controllers boards.
- Alerts are set to user if required.
- Event scheduling is possible.
- Supports many features with MATLAB.
Steps to follow:
- Create a channel which consists of data fields, location fields and status field.
- Then, write data to channel.
- Read data from the channel.
- Analyze and visualize the data.
- Furthermore act on the data.
- Finally, advanced analysis is performed in MATLAB if required.
Functionalities of ThingSpeak:
- The channel views like public view, private view or shared is depending upon the user requirements.
- The channel settings includes the Name, Description, Field, Metadata, Tags, URL, Channel location which includes the latitude and longitude.
- Likewise plots are also possible in ThingSpeak.
- The API keys is used to read from or write to the user channels.
- Similarly data import and export is also possible in ThingSpeak.
- Channel updates uses REST API and MQTT.
- REST API makes use of the GET, POST, PUT, and DELETE commands.
- Additionally Message Queuing Telemetry Transport publishes and subscribes to the messages.
New advancements in ThingSpeak:
- Libelium supports IoT by providing the sensor and gateway in the market which provides insights to the IoT data by visualization through the ThingSpeak with MATLAB.
- The histogram data is recorded which helps the user to analyze the performance of the devices.
- Moreover, MATLAB supports machine learning, system identification and algorithms related to signal and image processing for the ThingSpeak.
- A feed forward neural network gathers the data from the weather station and predicts the future data.
- Additionally, a recent study has been to count the people using face detection using ThingSpeak with Math Works.
- Finally the tag feature helps in identification of related channels. The matched channels can be very useful for the enterprise systems.
Applications of ThingSpeak:
- MATLAB analysis.
- MATLAB Visualizations.
There are various license options in ThingSpeak –
Moreover it has free service for small projects which are non commercial. Most importantly it gives approximately 8200 messages per day and less than 3 million per year if your project is non commercial. For commercialization application, we can take up either of the license options. If the project is large, we prefer MathWorks support requirement, While if we need unlimited private channel sharing we choose for the Standard license. To know more details about it, click the link below.
To know about the academic license check out the link below.
If you are student and want to commercialize your project check the ThingSpeak license below.
For personal use commercialization check the link below.
Concluding, this was the Internet of Things Implementation using ThingSpeak with MATLAB. We hope you liked this article. Moreover, please let us know if you have any suggestions. We at Eckovation love to hear your feedback.