72 lines
3.4 KiB
Markdown
72 lines
3.4 KiB
Markdown
# EvacSim
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EvacSim is a deterministic simulation that uses graph theory and linear
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programming to model the effects of hurricanes on communities in order to
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predict optimal evacuation routes. This project was originally developed for
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HackRPI 2019, a 24-hour hackathon in which it won 2nd place.
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## Background
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This project was originally developed for HackRPI 2019, a 24-hour hackathon in
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which it won 2nd place. The idea was born after witnessing the devastating
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effects of Hurricane Dorian as well as hearing from friends and family in
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tropical regions who were forced to evacuate their homes due to storms numerous
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times over the years.
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## How it works
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### Model
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In the model, populations are represented by nodes and the infrastructure
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between them are represented by edges. These nodes and edges can then be used
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to construct a graph. The actual modeling happens in CSV files, such as the
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following `nodes.csv` file modeling populations around Troy, NY:
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| Enabled | Name | Latitude | Longitude | Population | Capacity |
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| ------- | ------------- | -------- | --------- | ---------- | -------- |
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| 0 | Troy | 42.718 | -73.687 | 50000 | 60000 |
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| 0 | Albany | 42.649 | -73.753 | 98000 | 120000 |
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| 0 | Guilderland | 42.702 | -73.909 | 36000 | 50000 |
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| 0 | EastGreenbush | 42.588 | -73.703 | 16000 | 30000 |
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| 0 | Brunswick | 42.732 | -73.562 | 16000 | 35000 |
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| 0 | Schenectady | 42.806 | -73.943 | 65000 | 70000 |
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Similar models exist for edges, hurricanes, and the main setup:
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- `edges.csv`: Models infrastructure (ie. roads) between populations by source
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node, destination node, transit time, and maximum capacity.
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- `hurricanes.csv`: Models the hurricane by initial position, wind speed
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variation, velocity, and trajectory.
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- `main.csv`: Models the start and end time for the simulation.
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Examples can be found in the [models](../models/) folder.
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### Simulation
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The simulation has three main parts: the simulator itself, which is written in
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Java, the AMPL model, and the boilerplate script, which is written in
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JavaScript with Node.js. The script first fetches the model files from where
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they are stored in the IBM cloud. The files are then passed to the simulator,
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which translates the model files to usable data. From the hurricane data, the
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path and area of effect of the storm is determined, which is then used to
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determine which populations should evacuate. The data for edges, nodes, and
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affected nodes are then passed to an AMPL model which runs a minimum flow
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algorithm on the graph to determine where each affected population can evacuate
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to without violating maximum capacities on communities and infrastructure. This
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data is passed back to the Java simulation, which generates a KML file showing
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the area of effect of the hurricane, the severity in each region, the evacuation
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routes for each affected community, and data such as the final populations in
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each community. This KML file can be displayed in a geographic browser such as
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Google Earth.
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## What's next
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Some possibilities for extensions of the project include:
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- Supporting multiple types of natural disasters, such as earthquakes and
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wildfires
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- Improving the accuracy of hurricane representations by allowing for varying
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velocities and trajectories
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- Using IBM Cloud services more extensively
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- Creating a custom frontend to display evacuation routes rather than
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generating KML files
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