DCF-ENGINE | Climate Forensic Demonstration Console

Automated Disinformation Detection, Sensor Sanitization & Strategic Integrity Audit
Hackathon Track: Topic 3 (Mis-/Dis-information)
Status: Deterministic Engine Online

1. Ingested Municipal Document (Simulated Case Study)

[INGESTION FILE: City_Decarbonization_Report_Q3.pdf]
• Target Sector: Urban Transit & Municipal Grid
• Self-Reported Reduction: claimed -42% GHG (Target Met)
• Ground Sensor Reality: physical -14% GHG (Structural Gap Detected)
• Fuel Consumption Sensor Feed: Injected Outlier Spike +18% (Poisoned Ingestion)
• Forensic Determination: Greenwashing Metric Inflation & Sensor Drift Discovered.
Simulated degree of reporting bias, ESG padding, or sensor noise
Vectorized hard data extracted from municipal telemetry and energy grids
Deterministic parsing depth and automated structural gap extraction
Municipal Climate Integrity Index:
Vulnerable: High Distortion Detected
0.92 Index

2. Forensic Integrity & Topological Resilience

3. Automated Deterministic Audit Log

Verification Vector Status Forensic Action
Self-Reported ESG Claims DISCREPANCY (28%) Flagged for Municipal Re-evaluation
IoT Sensor Streams SANITIZED Poisoned packets isolated from model
Audit Trail Signature DETERMINISTIC SHA-256 Immutable Audit Hash Created
Architectural Authority: Eman El Shafie | Genesis Logic Lab | Eudaimonics Theory Founder
AI x City Climate Action Hackathon 2026 Demonstration Appliance | Topic 3: Climate Mis- / Dis-information