"This is South Bronx, New York City (Region specific prototype based on my research, this is most visible and vulnerable to inequality of land use). The red you're seeing is not traffic. It's not heat. It's a computational model of years of accumulated socio-economic inequality, the Feral Agent."
"Before the highway, the neighborhoods through which Moses would build the Cross Bronx were among the most racially integrated in the country, with large populations of Jewish immigrants from Eastern Europe, Irish and Italian Immigrants, (and after WWII) Puerto Ricans, and African-Americans. After the highway tore through, property values plummeted. White residents fled (lured to the suburbs by government-backed mortgages), while black and brown residents remained (oftentimes with few other options due to red-lining and racist housing policies). As covered in the documentary, Decade of Fire, subsequent disinvestment in services from the city led The Bronx to burn in the 70s and 80s, destroying roughly 80% of housing stock and displacing another 250,000."
Traditional tools (GIS, census) can't show the algorithmic logic of how infrastructural violence propagates through time and space.
- Feral Agent concentrated along highway corridor
- Inherited displacement and disinvestment
- Violence that spreads, compounds, and becomes systemic
Don't Flush Me
Data visualization of NYC's combined sewer overflow system
Feral Web
Decentralized web infrastructure project
Emissary's Trilogy
Narrative exploration of infrastructure and power
Vanessa Agard-Jones
Anthropological work on toxicity and environment
FERAL AGENT
NOT A Human/Resident
The agent is not an individual person, household, or demographic group. It transcends individual human experience.
NOT Physical Infrastructure
Not a road, building, pipe, or tangible object. It exists in computational space as an abstraction.
IS A Digital Proxy
A computational representation of accumulated vulnerability that can be simulated, measured, and analyzed.
TECHNICAL FLOW
Input/Logic Layers
Core framework components and logic processing units.
Data Sources
Historical and real-time data inputs feeding the system.
Core Algorithms
Computational engines driving the analysis.
Processing Functions
Specialized functions for data transformation.
TECHNICAL PRECEDENTS
AGENT-BASED MODELING VISUALIZATIONS
Mathematical Prediction Model
Demonstrates the predictive capabilities of the ABM system, showing how agents evolve over time based on mathematical rules.
Interactive Simulation
Shows real-time agent interactions and emergent patterns in the simulation environment.
Ternary Logic System
Implements a three-state logic system for agent decision making, allowing for more nuanced behavior representation.
State Transitions
Visual representation of how agents transition between different behavioral states based on environmental factors.
Decision Matrix
Shows the decision-making framework that guides agent behavior in different scenarios.
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Precision
Replaces guesswork with a calculated "Jurisdiction of Risk" for targeted zoning.
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Prediction
Tests policies via simulation before implementation to prove they work.
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Enforcement
Automates instant evidence for fines, removing human delay and bias.
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Democratization
Turns invisible pollution into visual proof for community leverage.
"The Map targets the risk.
The Simulation validates the solution.
The Alert enforces the law."
// Simple boolean switch
const interventionActive = true; // Toggle effect
const getSensorReading = () => interventionActive ? 15 : 45; // Safe or Violation
The Purple Box becomes a Damping Zone
- Action: Multiplies particle speed by 0.05 (95% reduction)
- Visual: Particles "freeze" upon hitting the wall
Represents a CLT Green Wall physically blocking and filtering PM2.5.
"The Buffer activates a Damping Function (β) that physically slows particle velocity, forcing the sensor reading down to a safe 15."
This system aligns with Permacomputing by prioritizing radical efficiency and lifespan over excess.
The Tech:
The simulation runs on a single, lightweight HTML file with vanilla JavaScript—not a heavy engine like Unity or Unreal.
The Benefit:
It requires negligible processing power, meaning it can run on 10-year-old laptops or low-end mobile devices, extending hardware lifespans.
The Tech:
The "Forensic Node" logic is designed for low-power microcontrollers (Raspberry Pi/ESP32).
The Benefit:
It consumes minimal wattage, allowing the sensors to run indefinitely on small solar panels off the grid.
The Tech:
It uses simple geometric primitives (dots, lines) instead of photorealistic rendering.
The Benefit:
It prioritizes clarity over computational cost, reducing the carbon footprint of the digital tool itself.
"The medium matches the message: A system designed to protect the environment is built on code that respects environmental limits."
This visualization demonstrates how permacomputing principles are applied in our system, showing the efficient use of resources and sustainable computing practices.