Agentic Counter-Surveillance Analysis

This project is an attempt to create a pipeline with independent AI agents to do counter-surveillance analysis. This multi-agent system, uses publibly available data from OpenStreet maps, to analyze surveillance infrastructure. 

The project has two agents, up until now, has two agents.

• Scraper Agent: Downloads surveillance data from OpenStreetMap via Overpass API
• Analyzer Agent: Enriches data using local LLM analysis and generates visualizations

The analysis can produce:

• Heatmaps, to get an idea of the density of the infrastructure 
• Surveillance hotspots, using a DBSCAN algorithm
• Summary statistics, for camera types, operators, surveillance zones.

Under the hood the project uses a LLM and the system operates completely locally without external APIs focusing on a private and secure manner and the agents have internal memory.

Currently the agents can accessed via a Command Line Interface (CLI).

Next steps, include the development of an intuitive User Interface (UI) and a third path finding agent that will try to find routes that are not heavily surveilled, if any.

For more information on usage, you can read the README file.

Below are some examples of the system's outputs:

The source code of the project is open source and lives over at GitHub:

https://github.com/jethronap/UNDO-agentic

The UNDO Team.