The Optimization for Networked Data in Environmental Urban Waste Collection (ONDE-UWC) project is, to our knowledge, the first attempt to apply the Internet of Things (IoT) paradigm to the waste collection field. Sensors installed on dumpsters and garbage trucks share data, such as the number of user accesses and weight measures. In this study, we schedule the weekly waste collection activities of all the types of waste without imposing periodic routes. An important characteristic of this project considers the network presence of heterogeneous stakeholders with different background knowledge. In this context, we apply the GUEST OR methodology, highlighting how it can support the decision-making process in order to reduce this gap. This will bring positive consequences in terms of reduced time for solution implementation, followed by operational efficiency and economical savings.

Waste collection in urban areas: a case study / Fadda, Edoardo; Gobbato, Luca; Perboli, Guido; Rosano, Mariangela; Tadei, Roberto. - In: INTERFACES. - ISSN 0092-2102. - STAMPA. - 48:4(2018), pp. 307-322. [10.1287/inte.2018.0943]

Waste collection in urban areas: a case study

Fadda, Edoardo;Gobbato, Luca;Perboli, Guido;Rosano, Mariangela;Tadei, Roberto
2018

Abstract

The Optimization for Networked Data in Environmental Urban Waste Collection (ONDE-UWC) project is, to our knowledge, the first attempt to apply the Internet of Things (IoT) paradigm to the waste collection field. Sensors installed on dumpsters and garbage trucks share data, such as the number of user accesses and weight measures. In this study, we schedule the weekly waste collection activities of all the types of waste without imposing periodic routes. An important characteristic of this project considers the network presence of heterogeneous stakeholders with different background knowledge. In this context, we apply the GUEST OR methodology, highlighting how it can support the decision-making process in order to reduce this gap. This will bring positive consequences in terms of reduced time for solution implementation, followed by operational efficiency and economical savings.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2668766
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