Project Overview

Objective: Develop a mobile application that uses AI to detect Cambodian artifacts and provide detailed historical explanations. The app will be available on iOS and target both Cambodians and tourists.

Key Features

1. Artifact Detection:
   • Use computer vision to identify and recognize Cambodian artifacts.
   • Employ deep learning techniques to train the model on various artifacts and historical sites.
2. Historical Explanations:
   • Use a multimodal approach combining visual recognition with a language model to generate detailed explanations.
   • Provide audio and text prompts to make the information accessible and engaging.
3. User Interface:
   • Develop an intuitive iOS app that allows users to point their camera at artifacts and receive immediate feedback.
   • Include features such as saving favorite artifacts, sharing discoveries on social media, and accessing more detailed information.

Implementation Steps

1. Data Collection

• Gather Images: Collect a large dataset of images of Cambodian artifacts and historical sites. This can include statues, carvings, temples, and more.
• Annotation: Label the images with relevant metadata such as the name of the artifact, historical significance, location, etc.
• Augmentation: Apply data augmentation techniques to increase the diversity of the training dataset, ensuring the model is robust against various lighting conditions, angles, and occlusions.

2. Model Development

• Object Detection Model:
  • Use pre-trained models like YOLO (You Only Look Once), SSD (Single Shot MultiBox Detector), or Faster R-CNN to detect artifacts.
  • Fine-tune the model on the collected dataset to improve accuracy and recognition capability.
• Multimodal AI:
  • Combine the object detection model with a language model (such as GPT-3 or GPT-4) to generate detailed explanations based on the detected artifact.
  • Train the language model using a dataset of historical descriptions and context-specific information about Cambodian artifacts.

3. Mobile App Development

• iOS App Development:
  • Use Swift and SwiftUI to develop the mobile application.
  • Integrate the object detection model using Core ML or TensorFlow Lite for on-device inference to ensure fast and reliable performance.
  • Develop a user-friendly interface that allows users to scan artifacts and receive detailed explanations.
• Features to Include:
  • Real-Time Detection: Users can point their camera at an artifact to get instant recognition and information.
  • Audio Narration: Provide audio explanations for a more immersive experience.
  • Offline Mode: Allow users to download data for offline use, ensuring functionality without internet access.
  • Social Sharing: Enable users to share their discoveries on social media.

4. Testing and Validation

• Beta Testing: Conduct beta testing with a group of users, including locals and tourists, to gather feedback and identify areas for improvement.
• Performance Evaluation: Measure the accuracy, speed, and user satisfaction of the app. Continuously improve the model based on user feedback and performance metrics.