SARarvot

SARarvot is a modular open-source software platform designed for the simulation and optimization of search and rescue operations. It integrates multi-agent modeling with geographic information systems (GIS) and stochastic weather models to support planning, training, and after-action analysis. The name blends the common acronym SAR with a constructed suffix, and is used across the platform’s documentation and user community.

Development began in the late 2010s as a collaborative effort among researchers and practitioners in emergency management. The project released a core agent-based modeling engine, GIS integration, and a scripting interface for designing scenarios. Subsequent versions expanded data interoperability, scalability for large simulations, and visualization capabilities.

SARarvot comprises an agent-based core, a GIS data layer, and a scenario engine. Users define agent types such as search teams, unmanned aerial vehicles, and ground vehicles; environmental layers including terrain, weather, and visibility; and objectives like sector probing and target location. The platform supports stochastic runs, sweeps of parameters, and optimization routines, and it can export results to charts and tabular data.

It is used for training responders, planning resource deployment, validating response strategies, and researching sensor placement and decision-making under uncertainty. The platform is employed in academic exercises and formal emergency-management drills, as well as by professional agencies for scenario analysis.

Comparable platforms such as NetLogo, MASON, and GAMA are often cited in discussions of SARarvot’s capabilities and potential applications.