ROSHAN (Rescue Oriented Simulation: Handling and Navigating Fires), is a wildfire simulation tool. ROSHAN integrates the principles of cellular automata with reinforcement learning to simulate wildfire dynamics and automatic handling. entral to this simulation tool is its rendering and simulation of fire spread, achieved by integrating data from the CORINE database. The interactive graphical interface of ROSHAN facilitates real-time monitoring and manipulation of fire scenarios. A key component in ROSHAN is the incorporation of a Reinforcement Learning agent, embodied as a drone, which learns to detect and mitigate fires.

You can read everything about the development here.

These modules go under externals:

https://github.com/ocornut/imgui

https://github.com/aiekick/ImGuiFileDialog

https://github.com/nlohmann/json

sudo apt install libpython3.9-dev

https://github.com/pybind/pybind11

cd openstreetmap

npm install express body-parser

npm install --save-dev nodemon

Download Corine CLC+ Backbone - 10 meter (Year 2018)

https://land.copernicus.eu/pan-european/clc-plus/clc-backbone/clc-backbone?tab=download

Move *CLMS_CLCplus_RASTER_2018_010m_eu_03035_V1_1.tif to /CORINE/dataset/

Install GDAL and GDAL C++ headers

sudo apt install libgdal-dev gdal-bin libsdl2-image-dev

Install SDL2 according to:

https://github.com/libsdl-org/SDL/releases/tag/release-2.26.5 https://github.com/libsdl-org/SDL_image/releases/tag/release-2.6.3

conda create --name roshan python=3.9 libffi==3.3

conda activate roshan

pip install torch torchvision

conda install tensorboard

conda install packaging

pip install transformers[torch] onnxruntime bitsandbytes optimum onnx

cd \ROSHAN

mkdir build && cd build

cmake .. && make -j&(nproc)

cd build

./ROSHAN

cd drone_agent/FireSimAgent

python main.py