Check out our latest solution tutorial that helps you analyze data and detect anomalies in the historical data.
There are many use cases that may need multiple cloud services to work hand-in-hand. One such use case is where you set up an IoT mobile device, gather the sensor data in the Watson IoT Platform, explore data and create visualizations, and then using advanced machine learning services to analyze data and detect anomalies in the historical data.
We worked and published a solution tutorial that helps you go through such a use case in simple steps. Simply register and connect your device (be it a sensor, a gateway, or something else) to the Watson IoT Platform and start sending data securely up to the cloud using the open, lightweight MQTT messaging protocol.
You can set up and manage your devices using your online dashboard or our secure APIs so that your apps can access and use your live and historical data.
IBM Watson Studio provides you with the environment and tools to solve your business problems by collaboratively working with data. You can choose the tools you need to analyze and visualize data, to cleanse and shape data, to ingest streaming data, or to create and train machine learning models.
Set up IoT Simulator to collect mobile device sensor data.
Send collected data to Watson IoT Platform.
Create visualizations with a Jupyter notebook.
Analyze the device-generated data and detect anomalies.
Check out our other solution tutorials that guide you on how to build, deploy, and scale real-world solutions on IBM Cloud. These solution guides provide step-by-step instructions on how to use IBM Cloud to implement common patterns based on best practices and proven technologies.