Life improving for color blinds using Al and IoT
تفاصيل العمل
The Color Blind Assistance System is an innovative assistive technology designed to support individuals with color vision deficiency by enabling them to accurately identify and distinguish colors in their surroundings. The system integrates Artificial Intelligence (AI), specifically Convolutional Neural Networks (CNN), with Internet of Things (IoT) technologies to deliver a smart, real-time solution.
Using a color sensor, the system captures data and processes it through a CNN-based deep learning model to classify colors with high accuracy. The results are displayed on a 16×2 LCD screen, ensuring that users can easily interpret the identified color in text form.
To enhance scalability and reliability, the system is connected to a Firebase backend, which manages real-time data storage, updates, and secure cloud-based operations. This integration enables seamless performance, cross-device accessibility, and future enhancements such as voice feedback or mobile app integration.
Key Components:
LCD 16×2: Displays detected color names or descriptions.
ESP8266 Wi-Fi Module: Provides wireless connectivity and IoT integration.
CNN Model: Ensures accurate color classification using AI-based image recognition.
Firebase Backend: Offers real-time database, cloud storage, authentication, and scalable infrastructure.
Benefits:
1. Accessibility: Empowers individuals with color blindness to interact more effectively with their environment.
2. Accuracy: CNN-based classification provides precise color recognition.
3. Scalability: Firebase integration ensures seamless updates and potential expansion with mobile and voice-enabled features.
4. Efficiency: Real-time detection and display minimize delays in daily usage.
Conclusion:
The Color Blind Assistance System demonstrates how combining AI and IoT technologies can deliver impactful assistive solutions. By improving accessibility and independence for color-blind individuals, this project highlights the potential of technology to address real-world challenges.