ISPRS-Annals

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences

ISPRS-Annals

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

2194-9050

Copernicus Publications

Göttingen, Germany

10.5194/isprs-annals-VI-4-W2-2020-111-2020

A VISUAL ANALYTICS OF MOVEMENT DATA OF A WASTE COLLECTION SERVICE: A TOOL FOR SMART CITIES

Moreno

¹ Hernandez

D. I.

² Moreno

² Caglioni

² Hernandez

J. T.

https://orcid.org/0000-0002-5035-4363

IMAGINE, Systems & Computing Engineering, Universidad de los Andes, Colombia

Université Côte d’Azur, CNRS, ESPACE, Nice, France

15 09 2020

VI-4/W2-2020 111 118

2020

This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/

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The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/isprs-annals-VI-4-W2-2020-111-2020.pdf

Solid waste management is an important urban issue to be addressed in every city. In the smart city context, waste collection allows massive collection of data representing movements, provided by satellite tracking technologies and sensors on waste collection equipment. For decision makers to take advantage of this opportunity, an analytical tool suitable for the waste management context, able to visualize the complexity of the data and to deal with different types of formats in which the data is stored is required.The aim of this paper is to evaluate the potential of an interactive data analysis tool, based on R and R-Shiny, to better understand the particularities of a waste collection service and how it relates to the local city context. The User-centered Analysis-Task driven model (AVIMEU) is presented. The model is organized into seven components: database load, classification panel, multivariate analysis, concurrency, origin-destination, points of interest and itinerary. The model was implemented as a test case for the waste collection service of the city of Pasto in the southwest of Colombia. It is shown that the model based on visual analysis is a promising approach that should be further enhanced. The analyses are oriented in such a way that they provide practical information to the agents or experts of the service. The model is available on the site <code>https://github.com/MerariFonseca/AVIMEU-visual-analytics-for-movement-data-in-R</code> .