Engineered for accountability at every step.
GreenLoop AI eliminates manual data entry and unverified assumptions. From computer vision to verified collection weigh-ins, every interaction is recorded.
One loop. Five connected actions.
A cohesive architecture connecting community reporting to audited institutional recycling outcomes.
AI Waste Classification
Leveraging server-side Gemini multi-modal vision models to inspect visual textures, distinguish recyclable polymers from municipal landfill streams, and flag hazardous items.
Test an example image in real time:
Detected HDPE and clear PET polymer containers. High purity recovery rating.
Direct to Campus Baler Stream #4. Segregate non-polymer caps.
Live Incident Mapping
Interactive spatial map of campus sectors with real-time status indicators. Color-coded markers distinguish reported, in-progress, and verified collection sites.
Collection Coordination
Route tasks to dedicated personnel with priority weighting, equipment checklists, and time-to-collection SLAs.
Task TSK-101: Life Sciences Dock
Assigned: Marcus Vance • Due 14:00
Task TSK-102: Student Union Patio
Assigned: Marcus Vance • Organics
Verification & Accountability
Every resolution mandates post-collection photographic evidence. Administrators review the audit trail before closing the incident loop.
• Overflow Confirmed
• Audited & ClosedEnvironmental Impact Analytics
Transparent metrics computed directly from verified incident closures: gross tonnage, segregation fidelity, recycling rate, and landfill diversion.
Diversion Rate
74.2%
Campus benchmark
Waste Diverted
2,108 kg
From regional landfill
Audit Index
100%
Verified with photo
Ready to test the live platform?
Access the demo dashboard with full incident triage, map filters, and collection tasks.