The Environmental Data Visualization System is an innovative project aimed at making complex environmental data accessible through visually intuitive AI-generated art. By leveraging custom-built sensor systems, the project captures real-time environmental data and transforms it into artistic visualizations, bridging the gap between technical information and broader public understanding.
The system is composed of several interconnected components:
- Data Collection: Utilizes three main sensor systems—Weather Station, Detection Box, and Air Quality Box—to gather data from different environments.
- Data Processing: Handled by the Raspberry Pi, which converts the collected data into natural language prompts for AI models.
- AI Image Generation: AI models such as DALL-E 3 and Stable Diffusion generate images based on the processed data.
- User Interaction: A web dashboard provides real-time data monitoring and an interface for viewing generated images.
Monitors weather conditions including temperature, humidity, wind speed, and rain. Data is sent to the MQTT server and then processed for visualization.
Tracks visitor movement in exhibition spaces, providing valuable data for generating visual representations of crowd patterns.
Measures indoor air quality by detecting harmful gases and environmental conditions, feeding data into the AI system for analysis and visualization.
To begin using the system, please refer to the detailed setup instructions provided for each component:
Copyright (c) 2024 Chen Ruan (zczqrua@ucl.ac.uk)
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