The inspiration for our project was to create a system that can simulate and generate an energy optimization to cut the excess emission of carbon due to inefficient energy usage in the urban areas as they contribute over 70% of global CO2 emissions largely due to inefficient energy use. (Dasgupta, S., Lall, S., & Wheeler, D. (2024, March 16). Cutting global carbon emissions: where do cities stand? World Bank Blogs. https://blogs.worldbank.org/en/sustainablecities/cutting-global-carbon-emissions-where-do-cities-stand#:~:text=Cities%20account%20for%20over%2070,constructed%20with%20carbon%2Dintensive%20materials.)
The system we built allows user to design and simulate urban layouts. This system will:
Enable energy-efficient city planning Help manage peak power demands through strategic energy storage placement Provide data-driven insights for sustainable urban development How we built it Using an engine in python, the script creates an interactive 3D environment where users can simulate urban energy consumption and distribution using various types of buildings, parks, and power sources. It integrates features like heatmap visualization, pathfinding for energy distribution, and dynamic updates based on usage patterns.
As this is a hackathon project, the obvious challenge we ran into is time as we want to make a somewhat functional and presentable project in a 2 days span. The other is the fact that we never use the ursine engine before.
Some accomplishments that we're most proud of are:
- Comprehensive simulation system
- Dynamic heat-map visualizations
- Adaptable energy models
- Seamless integration models
- Engaging animations
We learned to use 2d and 3d animation with ursina engine, how to use algorithms to path-find, a few of us are also a first-timer python user, and we learned to graph data. The most important thing is to split the workload to reach our goal in the short amount of time we were given.
Our big goal for Mesh Analytics is to bridge the gap between energy management and urban planning.