Where to Place Public Bins Using Footfall, Fill Levels and Collection Routes

Placement and collection are one decision

A public bin is badly sited if the collection route cannot keep it empty. That is why placement and scheduling should be designed as a single system, not two separate checklists. Fixed, calendar-driven routes tend to fail in exactly the two places that matter most: busy corridors where containers overflow before the next scheduled visit, and quiet streets where crews empty bins that are barely a quarter full.

The pattern shows up clearly in vendor-reported municipal projects. Edinburgh, a high-tourism UK city, saw bins in dense areas such as the Royal Mile and Princes Street fill rapidly while rigid routes still serviced half-empty bins elsewhere. After fitting sensors and switching to data-driven routing, the council reported roughly a 30% reduction in collection cost and about a 50% drop in overflow complaints. Treat such figures as directional evidence, not a guarantee for your network: outcomes depend on density, container volume and how inefficient your current routes are.

Watch both ends of the same trade-off. An extra trip to a half-empty bin burns fuel and crew time; a missed full bin produces litter, complaints and an unscheduled cleanup. Both failures are measured with the same instrument — data on actual fill.

• Over-servicing half-empty bins is hidden cost in fuel and labour.
• Under-servicing full spots drives litter, complaints and extra callouts.
• Both extremes become visible only when fill is measured.

Layer one — footfall: where people actually stop

Footfall is the first layer because bins belong where people pause, not where they simply walk past. Concentrate on natural stop points: benches and seating, entrances to shops and public buildings, transit stops, takeaway and food courts, playground edges, promenades and the pinch points around events and markets. Someone who is sitting, waiting for a bus or finishing food is far more likely to use a bin than a person moving through open pavement.

Trade-offs are real. More bins improve convenience but raise emptying cost, cleaning and visual clutter; fewer bins lower maintenance but invite littering where demand is spiky, such as near a shopping centre or stadium. Accessibility matters as much as density: a bin placed on the walking line can block wheelchair users and prams, so tuck it to the edge of the path and keep the route clear. Improvement codes in many municipalities explicitly prohibit such obstruction.

• Look for stop points: seats, entrances, stops, takeaway vendors.
• Keep bins off the walking line and preserve clear access.
• For spiky-demand zones, plan spare capacity or a reactive trip.

Layer two — fill level: what sensors reveal

Footfall predicts where litter appears but not exactly when a given container fills. Fill-level sensing closes that gap. An ultrasonic or radar sensor measures the distance to the waste inside and reports a fill percentage over a low-power network such as LoRaWAN, NB-IoT, Sigfox or CAT-M1 to a dashboard used by the operations team.

Vendor-reported deployments illustrate the effect. Prague equipped about 3,294 underground containers with ultrasonic sensors and reports that the average fill level at the moment of collection rose from roughly 45% in 2018 to about 71% in 2024, with an estimated saving of about $156 per bin per year. Madrid fitted about 11,100 sensors to bins for packaging, glass, textiles, organic and general waste in early 2023 to move away from fixed schedules. Buenos Aires started with about 2,000 sensors and expanded to about 4,500, using the data first to re-optimize placement and later to design a collection contract based on real demand.

Be sceptical of advertised savings. Some vendors caution that promises of cost reductions up to 70% are often overstated, and the real effect depends on how inefficient your baseline schedule is. Sensor readings are also noisy: loosely dumped waste makes percentages jump, so base decisions on trends and several readings rather than a single signal.

• A sensor reports fill percentage and flags when a threshold is crossed.
• Network and battery are part of the decision — verify radio coverage on site.
• Single readings are unreliable; follow trends and calibrate.

Layer three — the route: collect what is full

The third layer is the route. Instead of driving a fixed circuit, the operator clusters only the containers that have crossed an agreed fill threshold and builds a route for those stops. Trucks travel fewer kilometres and carry fuller loads, cutting fuel, emissions and noise.

Routing software needs navigation that understands service constraints, not ordinary car GPS. Madrid's deployment highlights routing adapted for waste vehicles across narrow streets, pedestrian zones and one-way roads, with drivers following turn-by-turn instructions and supervisors able to add urgent pickups or re-route for events. Choose the threshold realistically: emptying at 100% risks overflow on busy days, while emptying at 60% wastes trips. A starting point near 80% is common, then adjusted to local peak patterns.

• Cluster only stops that have crossed the fill threshold.
• Navigation must handle narrow streets, pedestrian zones and one-way roads.
• A threshold near 80% is a sensible starting point, tuned to local peaks.

Fit local codes and keep routes serviceable

Every placement must also satisfy local rules and remain physically serviceable. Municipal improvement codes in many jurisdictions set the framework: bins at each entrance to commercial and public buildings, near every bench in parks and squares, on transport stops, and along pedestrian corridors at a defined maximum interval. The improvement rules of Barnaul, used here as an example, specify bins 50–100 cm tall, near each bench and entrance, and never obstructing pedestrians or buggies.

Spacing floors are common: on main pedestrian communications bins are placed no more than about 60 m apart and on other municipal territory no more than about 100 m apart, in addition to mandatory points at benches and stops. Because such codes are set municipality by municipality and are frequently amended, verify the current version for your own territory before ordering equipment.

A location that meets the minimum spacing can still be unserviceable if a truck cannot reach it or a sensor has no network. Check turning space for vehicles, access for emptying and radio coverage during the audit, before anything is installed.

• Always check the current rules of your own municipality.
• Roughly 60 m on main routes and 100 m elsewhere is a common spacing floor.
• Regulatory minimum does not equal serviceability — verify access and network.

Pilot, calibrate, then scale

Resist instrumenting the whole city at once. Run a pilot on a sample of the busiest bins: over several weeks record overflow incidents, collection cost and fill patterns, then tune the fill threshold and confirm that the network and routing tool work in your setting before you scale. Buenos Aires illustrates this path: a smaller batch of sensors first, then expansion and use of the accumulated data to design a new collection model.

Where a sensor budget is tight, consider alternatives such as solar-powered compacting bins that raise effective capacity and cut the number of trips, provided there is reliable sun and anti-vandal protection — a climate-dependent choice.

The value of the system is the ongoing correction loop: footfall defines the starting layout, fill data relocates and resizes capacity, and routes continuously follow measured demand. Revisit the map at least seasonally, because festivals, new buildings and shifting commuter patterns move demand, and a layout that was right in spring can be wrong by autumn.

• Pilot on a busy sample: measure, calibrate, then scale.
• Compacting bins cut trips but depend on reliable energy and protection.
• Revisit the layout seasonally — demand shifts.