CASCADE | Immersive Disaster Response
Coordinated Agency Simulation for Catastrophic and Disaster Events
CASCADE is an immersive simulation framework designed for multi-agency coordination during large-scale crises. By integrating real-world data telemetry with story-centered environments, CASCADE provides a risk-free training ground for evaluating complex decision-making under extreme pressure.
CASCADE | Landfill Disaster Management
The West Ridge Scenario:
This module challenges users to investigate a localized public health crisis at a decommissioned landfill. As environmental directors and public health officials, participants must synthesize thermal drone data and radiological signatures to identify "orphaned nuclear sources" while a Category 3 hurricane approaches the site.
Core Mechanics: Aerial drone POV navigation, thermal grid scanning, and multi-agency communication relays.
The Escalation: A transition from environmental forensic investigation to infrastructure collapse as a hurricane triggers gas leaks, water contamination, and power grid failures.
Audio Pipeline: High-fidelity, AI-driven dialogue utilizing the Bark TTS framework for distinct character performances.
Upcoming Academic Deployment
Fall 2026 Integration | Rowan University
CASCADE: Landfill is currently slated for integration into the Rowan University Ric Edelman College of Disaster Science and Emergency Management curricula beginning in the Fall 2026 semester. The module will serve as a foundational immersive experience for students to practice high-stakes decision-making and multi-agency coordination, providing a data-rich environment for empirical learning and program evaluation.
CASCADE | Active Shooter @ Liberty State Park
Multi-Perspective Surveillance & Threat Detection
Currently in active prototype development, this module utilizes the landmark setting of Liberty State Park to train users in the critical window of time preceding an incident. Set in a high-density public environment, the simulation focuses on the detection of suspicious behavioral patterns and the deployment of investigative resources.
Multi-Perspective Observation: Participants can toggle between three distinct vantage points: Ground Level (on-foot perspective), Aerial Drone (low-altitude telemetry), and Tactical Helicopter (high-altitude wide-area oversight)—to monitor crowd dynamics.
Investigative Selection: Users can actively select individuals within the crowd to initiate targeted searches. This process reveals person-specific data, challenging the player to justify resource allocation based on observed behavioral indicators.
Active Threat Transition: Following the investigative phase, the simulation escalates into a dynamic active shooter scenario, testing the user's transition from surveillance to immediate crisis management.
Development Status:
This module is currently a high-fidelity prototype. Our team is refining the visuals, crowd AI, and the investigative data-overlay system to enhance the training efficacy for law enforcement and public safety personnel.