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By Krishna Prabu, Vishal Chahal, Balaji Kadambi | Published May 30, 2018
Once an anomaly is detected in an IoT system or sub-system using change point detection, a failure prediction based on predictive analytics models can identify an upcoming failure condition in advance. Based on this detection, a proactive prescriptive action can be taken. This proactive action in traditional applications are typically scheduled maintenance activities. Even though it is possible for us to predict and initiate actions using IoT sensor data, the edge layer is not always equipped with hardware that can receive such instructions and take the corrective action. In more advanced systems, the equipment supports such 2-way communication and the hardware is wired at the edge such that corrective actions can be initiated through the actuators.
This IBM Code pattern is a composite pattern that brings together the end-to-end flow of IoT analytics systems. This pattern focuses on sending decisions based on analytics insights to the edge for automated actions.
You can use this code pattern to experiment, learn, enhance, and implement a method for predicting equipment failure using IoT sensor data. Sensors mounted on IoT devices, such as automated manufacturing devices like robotic arms or process monitoring and control equipment, collect and transmit data on a continuous basis which is time stamped.
The first step in implementing this advanced IoT analytics system would be to identify if there is any substantial shift in the performance of the equipment using time series data generated by a single IoT sensor. For a detailed flow on this step, refer to the Detect change points in IoT sensor data pattern.
The next step after detecting a change point in one key operating parameter of the equipment is to try to predict if this recent shift will result in a failure of the equipment. For a detailed explanation of implementing a bivariate prediction algorithm using Python 2.0 software, refer to the Predict equipment failure using IoT sensor data pattern.
Finally, the last step is to analyze the data and determine if an action needs to be taken, and if so send the command for the corrective action to the IoT device on the edge. This pattern will provide the details for how to implement this last step in the end-to-end advanced IoT analytics system.
When you have completed this pattern, you will understand how to:
Find the detailed steps for this pattern in the README. The steps will show you how to:
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