Analyze IoT sensor data with machine learning
Project Complexity - Intermediate
Technology: IBM Cloud Application | Business Sector: Others
Project Description
Project Idea :
According to a study, there will be more than 55 billion IoT devices by 2025, up from about 9 billion in 2017. Machine learning for predictive capabilities is now integrated with most industrial IoT platforms, such as IBM IoT
For example, if a sensor detects excessive heat or vibration, it triggers an alert. If the same sensor is connected to the internet, then the data encountered by the sensor can also be leveraged to draw more insights and perform analytics for future use.
In this project, you need to build a model for sensor data using Auto AI and build a web application that is integrated to the model built. Any anomaly predicted from the sensor data coming from the IoT platform is displayed on the Web App
Services Used:
- IBM Watson Studio
- IBM Watson Machine Learning
- Node-RED
- IBM Cloud Object Storage
- IBM IoT Platform
Technical Architecture:
