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Sustainability • Food Waste Recycling

Grind2Energy (An Emerson Company)

IoT-Powered Food Waste Recycling at Scale

G2E

Project Overview

Program Duration
48 months (ongoing)
Active Sites
50+ locations nationwide
Equipment Type
Biodigester systems
Customer Segments
Grocery, University, F&B
7,400+
Tons Diverted
50+
Active Sites
95%
Equipment Uptime
2,500+
Tons CO₂ Avoided

About Grind2Energy

Grind2Energy, an Emerson company, provides commercial food waste recycling solutions that convert organic waste into renewable energy and fertilizer. Their proprietary biodigester systems are deployed at grocery stores, universities, corporate campuses, and food processing facilities, helping organizations meet sustainability goals while reducing waste disposal costs.

!The Challenge

Grind2Energy's biodigester systems require careful monitoring to ensure optimal operation. Each unit processes up to 2,500 lbs of food waste per day, but without real-time visibility, the operations team faced persistent challenges that threatened program success.

  • Tank overflows: Without level monitoring, tanks sometimes exceeded capacity, causing messy and costly cleanups
  • Motor failures: Grinder motors failed without warning, leaving sites unable to process waste for days
  • Inefficient routing: Collection trucks visited sites on fixed schedules regardless of actual fill levels
  • Reporting gaps: Customers wanted sustainability metrics, but manual data collection was unreliable
  • Troubleshooting delays: Service calls required on-site diagnosis, with MTTR averaging 72 hours
72 hrs
Avg mean time to repair
15%
Tank overflow rate
30%
Wasted truck trips

The Solution

Grind2Energy partnered with MachineCDN to deploy comprehensive IoT monitoring across their entire biodigester fleet. Each unit is now equipped with sensors that stream real-time operational data to MachineCDN's cloud platform, enabling predictive maintenance, optimized collection routing, and automated sustainability reporting.

Per-Unit Sensor Configuration

Tank Monitoring
  • • Ultrasonic level sensor (0-100%)
  • • Temperature probe (slurry)
  • • pH sensor (anaerobic health)
  • • Overflow float switch (backup)
  • • Daily throughput calculation
Motor & Pump Monitoring
  • • Grinder motor current (CT clamp)
  • • Transfer pump current
  • • Vibration sensor (bearing wear)
  • • Runtime hours counter
  • • Cycle count per day
System Health
  • • Door open/close sensor
  • • Power consumption (kWh)
  • • Ambient temperature
  • • Cellular signal strength
  • • Last heartbeat timestamp

Intelligent Features

Predictive Maintenance
Motor current trending detects bearing wear 2-3 weeks before failure
Smart Collection Routing
API integration with logistics platform triggers pickups only when tank >75%
Automated Sustainability Reports
Monthly PDF reports with tons diverted, CO₂ avoided, renewable energy generated
Overflow Prevention
Tank level >90% triggers immediate alert + auto-schedules emergency pickup
Remote Diagnostics
80% of issues diagnosed remotely via sensor data before dispatching technician
Customer Portal
White-label dashboard for end customers to track their sustainability metrics

Operational & Environmental Results

Operational Metrics

Equipment uptime82% → 95% (+16%)
Mean time to repair72 hrs → 18 hrs (-75%)
Tank overflow incidents15% → <1% (-93%)
Wasted truck trips30% → 8% (-73%)

Financial Impact

Service cost reduction$240,000/year
Logistics optimization$180,000/year
Prevented overflow cleanups$95,000/year
Total annual savings$515,000

🌱Environmental Impact (Cumulative)

7,400+
Tons of food waste
diverted from landfills
2,500+
Metric tons CO₂
emissions avoided
1.2M
kWh renewable
energy generated
890
Tons of organic
fertilizer produced

Environmental metrics calculated using EPA WARM Model methodology and verified by third-party auditor.

"MachineCDN transformed our operations from reactive to predictive. Before, we'd get a call that a unit was down and scramble to diagnose it on-site. Now, I often call the customer before they know there's an issue. Last week, we caught a grinder motor drawing 30% more current—classic bearing wear signature. We scheduled a proactive replacement and avoided 3 days of downtime. That's the power of real data."
TD
Tim Dunson
Director of Field Operations, Grind2Energy

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