Research

This comprehensive study explores how artificial intelligence can transform urban security by identifying potential threats in real-time through camera feeds and sensor networks.

Tobias AdaneResearch Lead

Mar 15, 2025

This research paper compares traditional emergency response systems with AI-enhanced alternatives, measuring response times, accuracy, and overall effectiveness in crisis situations.

An exploration of advanced computer vision algorithms for analyzing crowd dynamics and identifying anomalous behavior patterns.

This paper proposes ethical guidelines for implementing surveillance systems that respect privacy while maintaining security effectiveness.

Tobias AdaneResearch Lead

Dec 12, 2024

Research on using NLP to improve emergency response by analyzing and prioritizing communications during crisis situations.

MIT Media Lab

Collaborative research on urban sensing technologies and their applications in improving city safety and emergency response systems.

Stanford AI Lab

Joint development of machine learning models for real-time video analysis and threat detection in complex urban environments.

NYU Center for Urban Science

Research partnership focused on implementing and testing AI security systems in New York City, providing real-world validation of our technologies.

University of Buenos Aires

Collaboration on adapting AI security systems for Latin American urban contexts, with a focus on cultural and infrastructural considerations.