Smart City IoT Waste Bin Monitoring — AI Route Optimization for Sanitation
A LoRaWAN fill-level monitoring system across 3,000 smart bins in a metropolitan city, combined with AI collection routing — reducing truck trips by 35% and cutting sanitation costs by $1.2M/year.
⚠The Problem
A city's sanitation department was running collection trucks on fixed schedules — emptying bins regardless of fill level. 40% of bins emptied were less than 30% full; 15% of bins were overflowing before the truck arrived (missed collections). Trucks were making 800 trips/day, including 320 unnecessary trips to half-empty bins, wasting fuel, driver hours, and generating avoidable emissions.
💡Our Solution
We installed ultrasonic fill-level sensors on 3,000 municipal bins, each solar-powered and transmitting fill level every 30 minutes via LoRaWAN. A Python AI routing service (using Google OR-Tools) generates dynamic daily collection routes based on fill-level predictions, only dispatching trucks to bins forecast to reach 80%+ fill by end of day. Drivers receive optimized routes on a React Native app. The municipal dashboard shows real-time bin status city-wide, heat maps of collection demand, and daily route plans for all 40 collection trucks.
🔗System Architecture
Smart Bin Sensors (LoRa) → TTN → Node.js Backend → PostgreSQL + Redis → AI Routing → React Dashboard + Driver AppTech Stack
- Ultrasonic fill-level sensor (HC-SR04 / JSN-SR04T)
- ESP32 + LoRa module
- Temperature sensor (bin fire detection)
- Solar panel (self-powered)
- Tilt sensor (bin knocked over)
- LoRaWAN (city coverage via TTN)
- MQTT to cloud
- Node.js backend
- PostgreSQL (bin registry + fill history)
- Python AI routing service (OR-Tools)
- Redis (real-time fill levels)
- React fleet + bin dashboard
- AI-optimized route map (Mapbox)
- Driver mobile app (React Native)
- Municipal reporting portal
Key Features
Results Delivered
- 35% reduction in truck trips (800 → 520 daily)
- $1.2M/year fuel and labor cost savings
- Bin overflow incidents reduced by 80%
- Carbon emissions from collection reduced 35%
- 3,000 bins managed in real-time on one dashboard
Technologies
Who This Is For
Municipal corporations, waste management companies, smart city projects, shopping mall operators
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