Project Overview
CycleSphere is a digital ecosystem where users can upload images of their old items, and through AI recognition, receive curated remodeling ideas ranging from modern functional designs to artistic re-creations. We conduct comprehensive research on waste transformation data and utilize relevant internet databases to train our AI models, aiming to bridge the gap between waste and creativity.
Datasets Used
- Country-Level Waste Data: The waste situation in different countries
- Solid Waste Disposal Trends (2024): The disposal quantity of solid waste in Hong Kong during 2009 to 2024
- Sustainable Fashion Trends 2024: The companies' develop trends for sustainable fashion market around the world
Tool Used
- Looker Studio: Used for generating the project's graphs
The Dataset graphs & Analysis
Local Context
Hong Kong's solid waste statistics (2009-2024) generally show an upward trend.
Global Overview
The percentage of waste in different countries around the world. The shade of color corresponds to the amount of waste, with China having the highest percentage globally.
Economic Correlation
The relationship between national GDP and per capita waste volume. The data shown in the graph is positively correlated.
Material Breakdown
Waste composition analysis (e.g., Glass, Metal, Paper, Plastic) of the world's top ten GDP countries. Length represents the total proportion of this type of waste.
Corporate Strategy
The companies' develop trends for sustainable fashion market around the world. The data shows that only 33.6% of companies chose to reduce their investment in the sustainable fashion market.
Eco-Brand Landscape
The global distribution of sustainable brands, showing a widespread global interest.
Recycling Performance
The global recycling rates, with China ranking third. This shows a strong foundational infrastructure for recycling, which CycleSphere can leverage.