
Real-time fill data lets Varde empty remote waste containers only when needed, replacing fixed routes with demand-led collection.

Varde uses fill-level sensors in 30 large waste containers to plan routes by need, cutting trips, diesel use and costs.

Real-time fill data lets Varde empty remote waste containers only when needed, replacing fixed routes with demand-led collection.

Varde had replaced 160 small, often overfilled bins with 30 large semi-underground containers across beaches and rest areas. As the number of large containers grew, it became difficult to know which ones needed emptying. The municipality emptied all containers on each round, but the route was about 200 km and could no longer reliably be completed in one working day. Varde therefore needed a way to target collection trips more precisely.
The plan was to combine large containers with IoT fill sensors and supplier-managed data analysis. Instead of relying on fixed rounds, Varde would use fill-level alerts and reports to decide when and where to empty containers. The supplier handles platform operation, sensor maintenance and data processing, while municipal staff use the information for route planning.
Step 1
Varde used large semi-underground containers at beaches and rest areas to reduce overflow and manual handling compared with many small bins.
Step 2
Fill-level sensors were placed in all 30 containers to monitor how full each container was in real time.
Step 3
The supplier collects, processes and analyzes data through a digital platform and provides reports to municipal staff.
Step 4
Staff receive an automatic notification when a container reaches 70% fill level.
Step 5
Collection routes are planned around actual fill levels so the truck drives only to containers that need service.
21%
Reduction in waste collection trips.
1,6 ton CO2
Annual emissions avoided from one truck.
1.600 km
Annual driving avoided.
39.800 kr.
Estimated yearly operating savings.
Varde estimates that sensors avoid about eight collection rounds per year. Because each round is about 200 km, this equals 1,600 km less driving, 615 liters less diesel and about 1.6 tons of CO2 avoided. The avoided staff and vehicle time was valued at 39,800 kr. in 2022, exceeding the 30,000 kr. annual sensor cost. The municipality also reports fewer overfilled containers, improved citizen experience and less manual lifting.
“Potentialet er stort i kommuner med store geografiske områder, hvor der køres mange kilometer for at tømme containerne eller skraldespande.”
The case shows that sensor data works best when route distances are long and containers are costly to visit unnecessarily. Municipalities should define whether their main goal is CO2, cost, service quality or work environment, then test the business case. Staff training and an engaged project owner are important because early sensor projects can have teething problems.
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