Waste collection in smart cities: The frequency capacity problem

Detalhes bibliográficos
Autor(a) principal: Oliveira, André
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/20264
Resumo: This dissertation aims the design and implementation of algorithms for solving an optimization problem of container capacity versus collection frequency, taking advantage of the information about the waste volume in containers obtained through sensors. Initially, state of the art will be made relative to intelligent cities through the use of sensors and the areas where internet of things is best applied. Waste collection optimization problems studied in the literature will be reviewed. Subsequently, through data provided by sensors that measure the volume occupied in each container, a statistical analysis is done on the same in order to understand which critical containers (whose capacity becomes null with some frequency) and which secondary containers (whose frequency of collection could be reduced). Next, algorithms are created to solve the problem of container capacity versus collection frequency, new models of frequency capacity are generated and results are present. Finally, the models generated are validated through prediction models and conclusions are drawn about the performance of each of the presented algorithms.
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spelling Waste collection in smart cities: The frequency capacity problemData analyticsOptimizationInternet of thingsAnálise de dados -- Data analysisOtimizaçãoInternet das coisasGestão de resíduosSmart CitiesAlgoritmo -- AlgorithmThis dissertation aims the design and implementation of algorithms for solving an optimization problem of container capacity versus collection frequency, taking advantage of the information about the waste volume in containers obtained through sensors. Initially, state of the art will be made relative to intelligent cities through the use of sensors and the areas where internet of things is best applied. Waste collection optimization problems studied in the literature will be reviewed. Subsequently, through data provided by sensors that measure the volume occupied in each container, a statistical analysis is done on the same in order to understand which critical containers (whose capacity becomes null with some frequency) and which secondary containers (whose frequency of collection could be reduced). Next, algorithms are created to solve the problem of container capacity versus collection frequency, new models of frequency capacity are generated and results are present. Finally, the models generated are validated through prediction models and conclusions are drawn about the performance of each of the presented algorithms.Esta dissertação tem como objetivo o desenho e implementação de algoritmos para a resolução de um problema de otimização de capacidade de contentores versus frequência de recolha de lixo, tirando partido da informação do volume de resíduos nos contentores obtida através de sensores. Inicialmente será feito o estado da arte relativo a cidades inteligentes através da utilização de sensores e as áreas onde a internet das coisas é melhor aplicada. Serão revistos problemas de otimização de recolha de lixo estudados na literatura. Posteriormente, através de dados fornecidos por sensores que medem o volume ocupado em cada contentor, é feita uma análise estatística sobre os mesmos de forma a perceber quais os contentores críticos (cuja capacidade se torna nula com alguma frequência) e quais os contentores secundários (cuja frequência de recolha poderia ser diminuída). Em seguida são criados algoritmos para a resolução do problema de otimização de capacidade de contentores versus frequência de recolha de lixo, gerados novos modelos de capacidade frequência e são apresentados resultados sobre os mesmos. Por último, é feita a validação dos modelos gerados através de modelos de previsão e retiradas conclusões sob a performance de cada um dos algoritmos apresentados.2020-12-09T00:00:00Z2019-12-10T00:00:00Z2019-12-102019-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/20264TID:202462404engOliveira, Andréinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:40:05Zoai:repositorio.iscte-iul.pt:10071/20264Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:18:31.108192Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Waste collection in smart cities: The frequency capacity problem
title Waste collection in smart cities: The frequency capacity problem
spellingShingle Waste collection in smart cities: The frequency capacity problem
Oliveira, André
Data analytics
Optimization
Internet of things
Análise de dados -- Data analysis
Otimização
Internet das coisas
Gestão de resíduos
Smart Cities
Algoritmo -- Algorithm
title_short Waste collection in smart cities: The frequency capacity problem
title_full Waste collection in smart cities: The frequency capacity problem
title_fullStr Waste collection in smart cities: The frequency capacity problem
title_full_unstemmed Waste collection in smart cities: The frequency capacity problem
title_sort Waste collection in smart cities: The frequency capacity problem
author Oliveira, André
author_facet Oliveira, André
author_role author
dc.contributor.author.fl_str_mv Oliveira, André
dc.subject.por.fl_str_mv Data analytics
Optimization
Internet of things
Análise de dados -- Data analysis
Otimização
Internet das coisas
Gestão de resíduos
Smart Cities
Algoritmo -- Algorithm
topic Data analytics
Optimization
Internet of things
Análise de dados -- Data analysis
Otimização
Internet das coisas
Gestão de resíduos
Smart Cities
Algoritmo -- Algorithm
description This dissertation aims the design and implementation of algorithms for solving an optimization problem of container capacity versus collection frequency, taking advantage of the information about the waste volume in containers obtained through sensors. Initially, state of the art will be made relative to intelligent cities through the use of sensors and the areas where internet of things is best applied. Waste collection optimization problems studied in the literature will be reviewed. Subsequently, through data provided by sensors that measure the volume occupied in each container, a statistical analysis is done on the same in order to understand which critical containers (whose capacity becomes null with some frequency) and which secondary containers (whose frequency of collection could be reduced). Next, algorithms are created to solve the problem of container capacity versus collection frequency, new models of frequency capacity are generated and results are present. Finally, the models generated are validated through prediction models and conclusions are drawn about the performance of each of the presented algorithms.
publishDate 2019
dc.date.none.fl_str_mv 2019-12-10T00:00:00Z
2019-12-10
2019-10
2020-12-09T00:00:00Z
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TID:202462404
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dc.language.iso.fl_str_mv eng
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