Reference: More efficient collection resulting in cost savings

Waste monitoring Right Frequencies
Waste collection New Routes
2 municipalities Project Scale

Customer description

The customer is a private waste collection company servicing 2 municipalities located in close proximity. Both municipalities pickup waste with the same vehicle. Municipalities have large-capacity containers that require hydraulic arm.

Problem description

Current collection plan is not efficient. All containers within the municipality are pickedup by one route. The vehicle capacity is not used to the fullest and some containers are overflowing. Waste Monitoring with Smart Sensors have discovered that containers are just 24 % full when picked-up in Municipality A and just 45 % full when picked-up in Municipality B. (Average for 6 month period) The waste monitoring data clearly showed there is potential for improvement and new collection routes need to be calculated.

Expectations from Sensoneo

01 Fullness monitoring in bins
02 Calculation of new collection routes
03 Better quality of service for citizens
04 More efficient waste collection and cost savings

Our Collection Planning Engine can accommodate data from Smart Sensors, multiple rules and count in different variables such as filling cycles of containers, vehicle capacity, trash type, kilometres driven, costs and more.  The Engine is a result of in-house R&D. The idea is to maximize the waste collected per kilometre driven. In this case, data from Smart Sensors allowed us to adjust collection frequencies to collect fuller bins.

Tomas Vincze Waste Collection Management Division Director

Implementation

Sensoneo Waste Monitoring solution combines Smart Sensors, the Smart Waste Management System and the Citizen App. The Smart Sensors use ultrasound technology to measure the fill levels in containers and dumpsters several times a day and send the data to the Smart Waste Management System, a powerful cloud-based platform, via the Internet of Things (Sigfox, NB-IoT, LoRaWAN, GPRS).

 

All large-capacity containers were monitored by Single Sensor. The Sensor measures 24 times a day how full is the container and sends the data via LoRaWAN network to Sensoneo backend. The Operator can follow the latest measurements in the Dashboard, part of Smart Waste Management System.

 

 

The Smart Waste Management System, a powerful cloud-based platform on Microsoft Azure, offers Waste Monitoring features such as detailed container inventory, digital interactive map, sensor configuration, display of live data from Smart Sensors, future predictions on fill levels, different notifications – fire and tilt alarm, citizen feedback and manual itinerary planning for waste collection.

We were collecting the data from Smart Sensors for 6 months without any adjustments to collection frequencies or routes. 

63% cost savings in Municipality A

Before

The collection frequency was set to 1x per 30 days (or 12x per year). All containers are collected by 1 collection route. The Smart Sensors were deployed and data collected over a 6-month period shows clearly that containers are just 24 % full when collected.

 

After

After reviewing the average fill level in containers, we recommend to adjust collection frequency and organize more than just one collection route to service all containers. Recommend frequencies are:

  • Route 1: 1x every 2 months
  • Route 2:  1x every 4 months
  • Route 3: 1x every 6 months

New routes resulted in 63 % cost savings.

 

43% cost savings in Municipality B

Before

The collection frequency was set to 1x per 60 days (or 6 x per year). All containers are picked-up by 1 pick-up route. The Smart Sensors were deployed and data collected over a 6-month period shows clearly that containers are just 45 % full when picked-up.

 

After

After reviewing the average fill level in containers, we recommend to adjust pick-up frequency and organize more than just one collection route to service all containers. Recommend frequencies are:

  • Route 1:  1x every 2 months
  • Route 2:  1x every 6 months

New routes resulted in 43 % cost savings.