Pi-Health: Digital Skin Disease Detection based on ML
In recent years, with the rapid development of computer-aided diagnosis (CAD) systems deep learning has been widely used for different tasks such as classification segmentation, and object detection. We are presenting here an idea of Pi-Health a Device using Machine learning at its backend to detect
2025-06-28 16:34:28 - Adil Khan
Pi-Health: Digital Skin Disease Detection based on ML
Project Area of Specialization Electrical/Electronic EngineeringProject SummaryIn recent years, with the rapid development of computer-aided diagnosis (CAD) systems deep learning has been widely used for different tasks such as classification segmentation, and object detection. We are presenting here an idea of Pi-Health a Device using Machine learning at its backend to detect skin disease at its early stage. We use a dual stage approach which effectively combines computer vision and deep learning clinically appraised histopathological attributes to accurately identify the disease. We propose a deep learning-based classification model for skin disease detection. Our proposed approach is simple, fast and does not require expensive equipment other than a raspberry pi 4. The approach works on the inputs of a color image, then resize of the image to extract features using Convolutional Neural Network. We validate the performance of the proposed method on the dataset.
Project ObjectivesThe thought behind this task is to make Pi-Health a non-obtrusive and cheap gadget that is utilized to catch excellent pictures of the affected patch of the skin and analyze which classification of skin disease it belongs. Early recognition of skin illness assumes a significant job in intense infections. So we could nip the issue in bud.
Project Implementation Method- Data augmentation
- Feature Extraction Algorithm
- Classifier
- Raspberry Pi Integration
- Portable device.
- Time efficient disease detection.
- Local availability at low rates.
Deployment of Deep Learning Model for skin disease detection on Raspberry pi.
GUI enabled Interface for easy reading.
Final Deliverable of the Project HW/SW integrated systemCore Industry HealthOther Industries Medical Core Technology Artificial Intelligence(AI)Other Technologies Clean TechSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 79500 | |||
| Raspberry pi 4 | Equipment | 1 | 25000 | 25000 |
| Laptop | Equipment | 1 | 30000 | 30000 |
| Pi Camera | Equipment | 1 | 1500 | 1500 |
| Raspberry pi LCD | Equipment | 1 | 8000 | 8000 |
| Battery backup | Equipment | 1 | 5000 | 5000 |
| Miscellaneous | Miscellaneous | 1 | 10000 | 10000 |