Prediction of Defective Photo-voltaic Module Cells using Machine Learning
Use of Solar Panels is increasing day by day. So in this Project we are going to apply Electroluminescence (EL) images technique to detect the defective cells of Photo-voltaic Module Cells. We will take pictures via cameras of solar panels. We will work on these images and compare t
2025-06-28 16:34:34 - Adil Khan
Prediction of Defective Photo-voltaic Module Cells using Machine Learning
Project Area of Specialization Artificial IntelligenceProject SummaryUse of Solar Panels is increasing day by day. So in this Project we are going to apply Electroluminescence (EL) images technique to detect the defective cells of Photo-voltaic Module Cells.
We will take pictures via cameras of solar panels. We will work on these images and compare the images of each cell using dataset we have. Then we will apply filters on each cell or use some machine learning techniques/algorithms like classification, Support Vector Machine (SVMs), SURF, SIFT, HOG. With these Filters and techniques, we will map out the defective cells and non-defective cells. Also we use a data logger device to store information of current probibility.In the end, we will apply probability on the detected/processed solar cells and predict the lifecycle of Photovoltaic Module Cells.
This will help to many industries of solar panel and home peoples who are using the solar panel to generate their own electricity.This application will help them to check the status of their solar panel and give information about its lifecycle.
Project ObjectivesOur objectives are to help the peoples, industries who are using solar panels.This application will help them to check the status of their solar panel and give information about its lifecycle.
Project Implementation MethodWe will take pictures via cameras of solar panels. We will work on these images and compare the images of each cell using dataset we have. Then we will apply filters on each cell or use some machine learning techniques/algorithms like classification, Support Vector Machine (SVMs), SURF, SIFT, HOG. With these Filters and techniques, we will map out the defective cells and non-defective cells.Also we use a data logger device to store information of current probibility. In the end, we will apply probability on the detected/processed solar cells and predict the lifecycle of Photovoltaic Module Cells.
Benefits of the ProjectThis Project will give the Benefit to the industries and the peoples who are using the solar panel system. This application will help them to check the status of their solar panel and give information about its lifecycle.
Technical Details of Final DeliverableA fully guided document about the application of the product that how to use it and how it will be helpfull etc.
Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther Industries Manufacturing , Others Core Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT), OthersSustainable Development GoalsRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 70000 | |||
| Solar panel System | Equipment | 1 | 24000 | 24000 |
| Max power point track (MPPT)er | Equipment | 1 | 10000 | 10000 |
| Current Sensor | Equipment | 1 | 2500 | 2500 |
| Voltage Sensor | Equipment | 1 | 2500 | 2500 |
| Wires | Equipment | 2 | 1000 | 2000 |
| Batteries | Equipment | 2 | 10000 | 20000 |
| Inverter (AC DC Load) | Equipment | 1 | 4000 | 4000 |
| Solar Panel Stand | Equipment | 1 | 5000 | 5000 |