AI-Enhanced Skin Cancer Screening with CNN on Edge Devices using Raspberry Pi
Objective
The objective is to develop a lightweight, real-time Raspberry Pi system using CNNs to detect skin cancer from images, enabling early diagnosis, affordable screening, and accessible healthcare.
Abstract
This project presents an AI-enhanced skin cancer screening system using Raspberry Pi, a web camera, and an LCD display. The web camera captures images of skin lesions, and a CNN-based deep learning model analyzes the images to classify them into four different skin disease categories. The processing is performed locally on the Raspberry Pi, enabling fast and privacy-preserving diagnosis without cloud dependency. The classification result is displayed on the LCD, providing a low-cost and portable solution for early skin disease screening and healthcare support.
Keywords: Raspberry Pi, Skin Cancer Detection, CNN, Edge AI, Deep Learning, Disease Classification.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Hardware components:
- Raspberry pi
- SD Card
- LCD
- USB Web camera
- Connectors-10.
Software requirements:
- Raspbian OS
- Python IDLE
Learning Outcomes
- Raspberry pi pin diagram and architecture
- How to install Raspberrypi / setup software
- Setting up and installation procedure for Raspberrypi
- Introduction to Raspberrypi environment / development setup
- Basic programming in Raspberrypi (Python)
- Basics of Embedded programming using Raspberrypi
- Basics of IoT platforms
- Working of power supply
- About Project Development Life Cycle:
- Planning and Requirement Gathering (software, tools, hardware components, etc.)
- Schematic preparation
- Code development and debugging
- Hardware development and debugging
- Development of the project and output testing
- Practical exposure to:
- Hardware and software tools
- Solution providing for real-time problems
- Working with team/individual
- Work on creative ideas
- Skills developed:
- Project development skills
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginative skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation skills
- Thesis writing skills
Paper Publishing
Request Call Back
Would you like to receive a free callback now?
Choose the best time for callback:
Leave your message and we will contact you as soon as possible
6-2-85/B, Old Maternity Hospital Road, Thyagaraja Nagar, Tirupati, Andhra Pradesh – 517501
+91 9030333433
+91 9393939065
0877-2261612
Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
