Use of domain knowledge to optimize the performance of an IoT-based waste collection service

Master Thesis (2022)
Author(s)

S. Giasoumi (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

Lóránt Tavasszy – Graduation committee member (TU Delft - Transport and Planning)

Gonçalo Homem Correia – Mentor (TU Delft - Transport and Planning)

Michiel de Bok – Graduation committee member (TU Delft - Transport and Planning)

Daan van den Elzen – Graduation committee member (Gemeente Rotterdam)

Jos Streng – Graduation committee member (Gemeente Rotterdam)

Faculty
Civil Engineering & Geosciences
Copyright
© 2022 Sofia Giasoumi
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Sofia Giasoumi
Coordinates
51.9244, 4.4777
Graduation Date
20-05-2022
Awarding Institution
Delft University of Technology
Programme
Civil Engineering | Transport and Planning
Faculty
Civil Engineering & Geosciences
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Abstract

Installing wireless sensors on a network of waste containers, that monitor at regular intervals their waste fill levels and transmit the data to the cloud of a waste management operator over the internet, describes the Internet of Things (IoT). With this constant stream of data, the dynamic organization of waste collection schedules is enabled as containers are visited for collection only when it is necessary, which consequently leads to demand-responsive services. Domain experts attest that operating a demand-responsive service brings financial and environmental gains to a waste collection service, but it simultaneously introduces complete variability in the system which is undesirable in real-life operations. To solve this problem and consequently optimize the waste collection service’s performance, domain experts stress the need for a balanced trade-off between dispatch consistency and flexibility. This means, being able to exploit to the highest degree possible the benefits of demand-responsive operations, while also maintaining a certain level of dispatch consistency when demand varies from day to day. This research focused on developing a solution approach to solve the IoT-based waste collection problem, which is derived from the knowledge and requirements of the domain. The use of the knowledge of the domain is significant as it ensures that the model is tailored and applicable to a real-life IoT-based waste collection service. The overarching objective of the approach is to maintain dispatch consistency and flexibility when the containers’ location and demands vary from day to day, as well as to attain an economically and environmentally enhanced waste collection performance.

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