Program Structure

Module 1: Food Waste Systems and Measurement

• Where food waste happens: production, storage, transport, retail, food service, households.
• Drivers: spoilage, overproduction, poor forecasting, packaging failures, and cold chain breaks.
• Metrics: shrink rate, spoilage rate, temperature excursion hours, FEFO compliance, and landfill diversion.
• Baseline assessment: auditing waste sources and defining measurable targets.

Module 2: Smart Sensors for Food Quality and Storage Conditions

• Core sensors: temperature, humidity, light exposure, vibration/shock, door-open events.
• Freshness indicators: gas/VOC concepts (ethylene, ammonia proxies), CO₂ monitoring basics (conceptual).
• Weight and load sensing: shelf/bin weight for consumption and depletion tracking.
• Calibration and accuracy: drift, placement effects, and quality assurance for sensor data.

Module 3: IoT Architecture for Food Waste Reduction

• System blocks: sensors → edge device → gateway → cloud platform → analytics → dashboard/alerts.
• Connectivity options: Wi-Fi, BLE, LoRaWAN, cellular—selection logic by environment and cost.
• Data design: time-series data, metadata, asset IDs, and event logging.
• Alert design: thresholds, escalation rules, and human-in-the-loop decisions.

Module 4: Cold Chain Monitoring and Compliance Logging

• Cold chain failure patterns: excursions, defrost cycles, door openings, and power outages.
• Monitoring design: sensor placement in trucks, cold rooms, and display units.
• Compliance logging: audit trails, exception reports, and corrective action workflows.
• Preventive maintenance signals: detecting equipment stress from patterns.

Module 5: Smart Inventory, FEFO/FIFO, and Demand-Aware Operations

• Inventory logic: FIFO vs FEFO and how sensors support shelf-life-aware decisions.
• Tagging concepts: QR/RFID basics and linking to batch/expiry metadata.
• Replenishment signals: integrating sales/consumption data to prevent overstocking.
• Operational workflows: receiving → storage → picking → disposal/donation pathways.

Module 6: Analytics for Spoilage Prediction and Intervention

• Data cleaning: missing data, outliers, drift, and sensor validation checks.
• Spillage/spoilage risk scoring: rules-based vs ML-based approaches (high-level).
• Time-series forecasting concepts: predicting temperature excursions, demand, and shelf-life decline.
• Interventions: dynamic pricing triggers, re-routing, restocking rules, and donation timing logic.

Module 7: Dashboards, Visualization, and Reporting

• Dashboard KPIs: waste reduced (kg), spoilage events avoided, cost saved, and carbon impact estimates.
• Heatmaps and maps: location-based risk monitoring for warehouses, routes, and stores.
• Operational reporting: shift reports, exception logs, and trend summaries.
• Stakeholder communication: translating sensor data into action and accountability.

Module 8: Security, Privacy, and Reliability Engineering

• IoT security basics: authentication, encryption concepts, and device access control.
• Data integrity: tamper evidence, audit logs, and reliable time-stamping.
• Uptime planning: redundancy, offline buffering, and graceful failure behavior.
• Maintenance: battery planning, recalibration schedules, and device replacement strategy.

Module 9: Implementation, Scale-Up, and Sustainability Impact

• Pilot design: choosing a site, defining scope, and setting success criteria.
• Rollout planning: training, SOPs, and change management for operational adoption.
• Impact measurement: baseline vs post-deployment comparison and uncertainty awareness.
• Circular pathways: donation networks, composting/biogas routing, and reporting frameworks.

Final Project

• Create a Food Waste Reduction IoT System Blueprint for a selected environment (retail store, warehouse, cold transport route, cafeteria, or community kitchen).
• Include: hotspot analysis, sensor plan, connectivity plan, data model, dashboard KPIs, alert rules, reliability/security notes, and rollout roadmap.
• Example projects: cold chain monitoring for a dairy route, FEFO-driven smart shelves for a supermarket, canteen waste tracking with weight + inventory analytics, or a warehouse spoilage early-warning dashboard.