Developing an indicators plan and software for evaluating Street Cleanliness and Waste Collection Services

Abstract

An app to evaluate the Street Cleanliness and Waste Collection Service was developed. This app is based on a Plan of Indicators that can be used to evaluate the Street Cleanliness and Waste Collection Service of Santander municipality. Specific methodologies for calculating and evaluating 59 indicators have been developed to obtain information regarding the status of the different elements of the service. The Plan of Indicators has been applied to Santander city. The app was designed to address, but is not limited to, the following goals: i) to obtain, store and calculate information regarding the above indicators and ii) to disseminate the results of the status of the elements of the Service to the public sector. The app that was developed can provide a quick view of the results obtained for each indicator in each district, which is useful for making an appropriate diagnosis of the city’s cleanliness and is the first step in the decision making and Service optimisation processes. Detailed results for the Street Cleanliness Index are shown for each district of Santander city. The Street Cleanliness Index values are also related to the Frequency Street Cleanliness Services parameters. Pearson correlation coefficient results suggest that an inverse relationship between the Street Cleanliness Index values and the Frequency Street Cleanliness Services/population density ratio exists (R2 = −0.63). The results show that Street Cleanliness Index worst values exist for those districts that have a lower Frequency Street Cleanliness Services /population density parameter. The results are useful for designing and optimising the Street Cleanliness Service. For the decision making process, resources should be allocated where necessary, which seems to be those districts with lower Frequency Street Cleanliness Services /population density ratios.

Keywords

• Street cleanliness
• Waste collection
• Performance indicators
• Resources optimisation
• Smart cities