All Case Studies
Case Study · 01

Somaiya Vidyavihar
University

Engineering Building, Mumbai  ·  R3BIN-SVU-001

Jan 20–30, 202610-Day PilotAI Waste SegregationEducation

664

Items Processed

10-day pilot

70%

Segregation Accuracy

Real-world conditions

21 kg

CO₂ Offset

Total across waste streams

94.2%

Recycling Rate

Materials diverted from landfill

The Challenge

Hundreds of items daily — no automated way to sort them.

Somaiya Vidyavihar University's Engineering Building handles high daily footfall of students and faculty. Waste was manually sorted, leading to contamination, compliance gaps, and zero visibility into composition patterns.

The Solution

One R3Bin unit. 10 days. Real-time AI classification.

Fostride deployed one R3Bin (R3BIN-SVU-001) powered by W.I.S.E. The system classified waste into Plastic, Paper, Metal, and Mixed in real time — with zero manual intervention and full timestamp logging for BRSR reporting.

Waste Composition

664 items classified

Plastic35%

233

CO₂ offset: 14.25 kg

Paper32%

212

CO₂ offset: 2.88 kg

Mixed31%

204

Landfill routed

Metal2%

15

CO₂ offset: 3.60 kg

Key Findings

Peak Day

Jan 23 saw 176 items classified in a single day — peak hours handled with no performance degradation.

ESG & BRSR Ready

Every event is timestamped and logged — enabling zero-manual-entry compliance reporting for ESG, CSR, and BRSR.

Phase 2 Target

Model fine-tuning on campus-specific data is targeting 80–90% accuracy, up from the 70% pilot baseline.

Environmental Impact

21 kg of CO₂ offset.
In 10 days. One bin.

Plastic recycling alone contributed 14.25 kg of CO₂ offset. Scaled to a full campus deployment, Fostride's R3Bin network delivers measurable, auditable climate impact — not estimates.

Want a pilot at your facility?

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