Smart Waste Collection System Based on Location Intelligence

Research output: Contribution to journalConference article in JournalResearchpeer-review

33 Citations (Scopus)

Abstract

Cities around the world are on the run to become smarter. Some of these have seen an opportunity on deploying dedicated municipal access networks to support all types of city management and maintenance services requiring a data connection. This paper practically demonstrates how Internet of Things (IoT) integration with data access networks, Geographic Information Systems (GIS), combinatorial optimization, and electronic engineering can contribute to improve cities’ management systems. We present a waste collection solution based on providing intelligence to trashcans, by using an IoT prototype embedded with sensors, which can read, collect, and transmit trash volume data over the Internet. This data put into a spatio-temporal context and processed by graph theory optimization algorithms can be used to dynamically and efficiently manage waste collection strategies. Experiments are carried out to investigate the benefits of such a system, in comparison to a traditional sectorial waste collection approaches, also including economic factors. A realistic scenario is set up by using Open Data from the city of Copenhagen, highlighting the opportunities created by this type of initiatives for third parties to contribute and develop Smart city solutions.
Original languageEnglish
JournalProcedia Computer Science
Volume61
Pages (from-to)120-127
ISSN1877-0509
DOIs
Publication statusPublished - 2015
EventProceeding of the Seventh International Conference on Intelligent Human Computer Interaction: IHCI 2015 -
Duration: 14 Dec 201516 Dec 2015

Conference

ConferenceProceeding of the Seventh International Conference on Intelligent Human Computer Interaction
Period14/12/201516/12/2015

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Electronics engineering
Graph theory
Combinatorial optimization
Geographic information systems
Internet
Economics
Sensors
Experiments
Internet of things
Smart city

Bibliographical note

DOI: 10.1016/j.procs.2015.09.170

Cite this

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title = "Smart Waste Collection System Based on Location Intelligence",
abstract = "Cities around the world are on the run to become smarter. Some of these have seen an opportunity on deploying dedicated municipal access networks to support all types of city management and maintenance services requiring a data connection. This paper practically demonstrates how Internet of Things (IoT) integration with data access networks, Geographic Information Systems (GIS), combinatorial optimization, and electronic engineering can contribute to improve cities’ management systems. We present a waste collection solution based on providing intelligence to trashcans, by using an IoT prototype embedded with sensors, which can read, collect, and transmit trash volume data over the Internet. This data put into a spatio-temporal context and processed by graph theory optimization algorithms can be used to dynamically and efficiently manage waste collection strategies. Experiments are carried out to investigate the benefits of such a system, in comparison to a traditional sectorial waste collection approaches, also including economic factors. A realistic scenario is set up by using Open Data from the city of Copenhagen, highlighting the opportunities created by this type of initiatives for third parties to contribute and develop Smart city solutions.",
author = "Lopez, {Jose Manuel Guterrez Lopez} and Michael Jensen and Andreasen, {Morten Henius} and Tahir Riaz",
note = "DOI: 10.1016/j.procs.2015.09.170",
year = "2015",
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language = "English",
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pages = "120--127",
journal = "Procedia Computer Science",
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}

Smart Waste Collection System Based on Location Intelligence. / Lopez, Jose Manuel Guterrez Lopez; Jensen, Michael; Andreasen, Morten Henius; Riaz, Tahir.

In: Procedia Computer Science, Vol. 61, 2015, p. 120-127.

Research output: Contribution to journalConference article in JournalResearchpeer-review

TY - GEN

T1 - Smart Waste Collection System Based on Location Intelligence

AU - Lopez, Jose Manuel Guterrez Lopez

AU - Jensen, Michael

AU - Andreasen, Morten Henius

AU - Riaz, Tahir

N1 - DOI: 10.1016/j.procs.2015.09.170

PY - 2015

Y1 - 2015

N2 - Cities around the world are on the run to become smarter. Some of these have seen an opportunity on deploying dedicated municipal access networks to support all types of city management and maintenance services requiring a data connection. This paper practically demonstrates how Internet of Things (IoT) integration with data access networks, Geographic Information Systems (GIS), combinatorial optimization, and electronic engineering can contribute to improve cities’ management systems. We present a waste collection solution based on providing intelligence to trashcans, by using an IoT prototype embedded with sensors, which can read, collect, and transmit trash volume data over the Internet. This data put into a spatio-temporal context and processed by graph theory optimization algorithms can be used to dynamically and efficiently manage waste collection strategies. Experiments are carried out to investigate the benefits of such a system, in comparison to a traditional sectorial waste collection approaches, also including economic factors. A realistic scenario is set up by using Open Data from the city of Copenhagen, highlighting the opportunities created by this type of initiatives for third parties to contribute and develop Smart city solutions.

AB - Cities around the world are on the run to become smarter. Some of these have seen an opportunity on deploying dedicated municipal access networks to support all types of city management and maintenance services requiring a data connection. This paper practically demonstrates how Internet of Things (IoT) integration with data access networks, Geographic Information Systems (GIS), combinatorial optimization, and electronic engineering can contribute to improve cities’ management systems. We present a waste collection solution based on providing intelligence to trashcans, by using an IoT prototype embedded with sensors, which can read, collect, and transmit trash volume data over the Internet. This data put into a spatio-temporal context and processed by graph theory optimization algorithms can be used to dynamically and efficiently manage waste collection strategies. Experiments are carried out to investigate the benefits of such a system, in comparison to a traditional sectorial waste collection approaches, also including economic factors. A realistic scenario is set up by using Open Data from the city of Copenhagen, highlighting the opportunities created by this type of initiatives for third parties to contribute and develop Smart city solutions.

UR - http://www.sciencedirect.com/science/article/pii/S1877050915030008

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JO - Procedia Computer Science

JF - Procedia Computer Science

SN - 1877-0509

ER -