EcoSpot
Industrial decarbonization, emission leak-point detection & circularity platform for Indian SMEs.
infoProject Overview
EcoSpot is an industrial decarbonization, emission leak-point detection, and circularity platform built for HackOut '26 at Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT). Designed for small and medium factories (SMEs) driving 40% of India's manufacturing output, EcoSpot transforms simple utility bills and shop-floor manifests into process-level digital twins. It isolates the top 20% of machines driving 80% of factory emissions, simulates what-if green retrofits with localized INR CapEx and payback velocities, provides an AI plant assistant, and compiles audit-ready SEBI BRSR Core and ISO 14064 compliance reports.
layersTechnology Stack
auto_awesomeKey Features
6 HighlightsPareto 80/20 Hotspot Detection
Isolates the vital 20% of machines, boilers, and processes generating 80% of factory emissions and material waste.
Visual Operational Flow & Sankey Mapping
End-to-end interactive energy and material flow diagram displaying inputs, machine conversions, losses, and circular recovery points.
Costed What-If Savings & Payback Simulator
Dynamic sliders for rooftop solar, biomass pellets, scrap remelting, and solvent distillation with localized INR CapEx and payback periods.
4 Calibrated Industrial Sector Presets
Grounded SME factory datasets for major Gujarat clusters: Surat Textile Mills, Rajkot Foundry, Ankleshwar Chemical, and Anand Dairy.
Grounded Factory AI Assistant
Domain-aware conversational advisor answering questions directly against factory numbers with one-click action chips.
SEBI BRSR Core & ISO 14064 Reports
One-click generation of official compliance filings and JSON manifests ready for bank credit facilities and government audits.
playlist_add_checkQuick Start Guide
$git clone https://github.com/sizwinz/EcoSpot.git && cd EcoSpot$.\start.ps1$cd backend && python -m venv venv && source venv/bin/activate && pip install -r requirements.txt && python run.py$cd frontend && npm install && npm run devBackend runs on port 8000; Frontend dashboard runs on port 5173.