Waste bin monitoring solutions are an essential step towards smart cities. This study presents an exploratory analysis of two waste bin monitoring approaches: (1) ultrasonic sensors installed in the bins and (2) visual observations (VO) of the waste collection truck drivers. Bin fill level data was collected from a Portuguese waste management company. A comparative statistical analysis of the two datasets (VO and sensor observations) was performed and a predictive model based on Gaussian processes was applied to enable a trade-off analysis of the number of collections versus the number of overflows for each monitoring approach. The results demonstrate that the VO are valuable and reveal that significant improvements can be achieved for either of the monitoring approaches in relation to the current situation. A monitoring approach based on VO combined with a predictive model is shown to be viable and leads to a considerable reduction in the number of collections and overflows. This approach can enable waste collection companies to improve their collection operations with minimal investment costs during their transition to fully sensorized bins.
Keywords: Smart cities; collection efficiency; monitoring solutions; service level; waste management.