Maximo Visual Inspection (MVI) is an add-on module for IBM's Maximo Enterprise Asset Management software that enables organizations to leverage AI and machine learning technologies to automate the inspection of assets and equipment. The solution uses computer vision algorithms to analyse images and videos captured by cameras or mobile devices, and identifies defects or anomalies in real-time.
In this use case we’ll see how we can identify Soiling of Solar Panels using MVI. Following the process steps to follow when working with MVI for this use case.
Prepare data set and label them as High and Low Irradiance level.
Once sample images are label, we augment the data set. After Augmentation of data set it is time to train the model and deploy it. Once model is deployed, we can do the testing of the model. For the testing, we take certain test images and either upload or drag/drop them. Model validates the condition and provide the output as per the images given to it with confidence.
For example – if we give image which less soiled solar panel, model validates and provide output as Low Irradiance level.
When we give image which high soiled solar panel, model validates and provide output as High Irradiance level.
Using Maximo Visual Inspection can be beneficial for organizations that have assets and equipment that require regular inspections, especially those in industries where safety and reliability are critical factors. The solution provides increased accuracy and efficiency, improved safety, predictive maintenance, enhanced data analytics, and increased compliance.
Author:
Prashant Sharma
Delivery Head - IBM Maximo & EAM360 Mobile App
