IoT applications in a smart city context
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/31381 |
Resumo: | Over the last few years, Smart City solutions mature very rapidly alongside IoT and cloud computing. These technologies made it easier to create services and incorporate applications devoted to improving citizen’s quality of life and offer ways for businesses to implement their solutions. Through rapid advances in the quality of sensors, new methods emerged, combining different types of devices to create a better picture of the environment. The purpose of this dissertation is to provide useful information thought public services, that can be accessed by people visiting or residing in the beach area of Costa Nova and Barra. It also provides a solution for the traffic classification problem that projects based on radar data tend to face. These applications take advantage of the devices implemented in the PASMO project, such as parking sensors, radars, and CCTV cameras. By making the service public, businesses have the opportunity to build applications on top of it, utilizing the sensor data without being directly connected to the data storage. The example developed in this dissertation offers a dashboard experience where users can navigate through charts that provide a variety of data and real-time maps. It also provides a public API that researchers and businesses can use to develop new applications in the context of PASMO. The other area tackled in this document is traffic classification. Although the data provided is reliable for the most part, one big issue is the accuracy of vehicle classification provided by the radar. Still, this device offers precise values when it comes to detection, with the cameras doing a good job in classifying traffic. The goal is to combine these two devices to present much precise information, using state-of-the-art object detection algorithms and sensor fusion methods. In the end, the system will enrich the PASMO project by making its data easily available to the public while correcting the accuracy problems of some devices. |
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IoT applications in a smart city contextSmart cityIotPasmoPlaftormPublic serviceSensor fusionOver the last few years, Smart City solutions mature very rapidly alongside IoT and cloud computing. These technologies made it easier to create services and incorporate applications devoted to improving citizen’s quality of life and offer ways for businesses to implement their solutions. Through rapid advances in the quality of sensors, new methods emerged, combining different types of devices to create a better picture of the environment. The purpose of this dissertation is to provide useful information thought public services, that can be accessed by people visiting or residing in the beach area of Costa Nova and Barra. It also provides a solution for the traffic classification problem that projects based on radar data tend to face. These applications take advantage of the devices implemented in the PASMO project, such as parking sensors, radars, and CCTV cameras. By making the service public, businesses have the opportunity to build applications on top of it, utilizing the sensor data without being directly connected to the data storage. The example developed in this dissertation offers a dashboard experience where users can navigate through charts that provide a variety of data and real-time maps. It also provides a public API that researchers and businesses can use to develop new applications in the context of PASMO. The other area tackled in this document is traffic classification. Although the data provided is reliable for the most part, one big issue is the accuracy of vehicle classification provided by the radar. Still, this device offers precise values when it comes to detection, with the cameras doing a good job in classifying traffic. The goal is to combine these two devices to present much precise information, using state-of-the-art object detection algorithms and sensor fusion methods. In the end, the system will enrich the PASMO project by making its data easily available to the public while correcting the accuracy problems of some devices.Nos últimos anos, as soluções Smart City amadurecem muito rapidamente em conjunto com IoT e serviços na cloud. Estas tecnologias facilitam a criação de serviços e a incorporação de aplicações direcionados á melhoria da qualidade de vida do cidadão, oferecendo formas das empresas implementarem suas soluções. Por meio de rápidos avanços na qualidade dos sensores, novos métodos surgiram, combinando diferentes tipos de dispositivos para criar uma melhor imagem da realidade. O objetivo desta dissertação é fornecer informações úteis através de serviços públicos, que podem ser acedidos por pessoas que visitam ou residem na Costa Nova e Barra. Também fornece uma solução para o problema de classificação de tráfego que projetos baseados em dados de radar tendem a enfrentar. Estas aplicações beneficiam dos dispositivos implementados no projeto PASMO, como sensores de estacionamento, radares e câmeras de CFTV. Ao disponibilizar os serviços publicamente, as empresas têm a oportunidade de construir as suas próprias aplicações em cima destes, usando os dados dos sensores sem estar diretamente conectado ao armazenamento de dados. O exemplo desenvolvido nesta dissertação oferece uma experiência de dashboard onde os utilizadores podem navegar por gráficos que fornecem uma variedade de dados e mapas em tempo real. Também fornece uma API pública que os investigadores e empresas podem usar para desenvolver novos aplicativos no contexto do PASMO. A outra área abordada neste documento é a classificação de tráfego. Embora os dados fornecidos sejam confiáveis, um grande problema provém da precisão da classificação dos veículos fornecida pelo radar. Ainda assim, este dispositivo oferece valores precisos quando se trata de detecção, com as câmeras fazendo um bom trabalho na parte de classificação do tráfego. O objetivo é combinar estes dois dispositivos para apresentar informações corretas, usando algoritmos de detecção de objetos e métodos de fusão de sensores. No final, o sistema irá enriquecer o projeto PASMO, tornando seus dados facilmente disponíveis ao público e corrigindo problemas de precisão de alguns dispositivos.2021-05-17T13:07:57Z2021-02-25T00:00:00Z2021-02-25info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10773/31381engOliveira, Rafael Fernandes deinfo: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:RCAAP2024-02-22T12:00:35Zoai:ria.ua.pt:10773/31381Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:03:16.720785Repositório 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 |
IoT applications in a smart city context |
title |
IoT applications in a smart city context |
spellingShingle |
IoT applications in a smart city context Oliveira, Rafael Fernandes de Smart city Iot Pasmo Plaftorm Public service Sensor fusion |
title_short |
IoT applications in a smart city context |
title_full |
IoT applications in a smart city context |
title_fullStr |
IoT applications in a smart city context |
title_full_unstemmed |
IoT applications in a smart city context |
title_sort |
IoT applications in a smart city context |
author |
Oliveira, Rafael Fernandes de |
author_facet |
Oliveira, Rafael Fernandes de |
author_role |
author |
dc.contributor.author.fl_str_mv |
Oliveira, Rafael Fernandes de |
dc.subject.por.fl_str_mv |
Smart city Iot Pasmo Plaftorm Public service Sensor fusion |
topic |
Smart city Iot Pasmo Plaftorm Public service Sensor fusion |
description |
Over the last few years, Smart City solutions mature very rapidly alongside IoT and cloud computing. These technologies made it easier to create services and incorporate applications devoted to improving citizen’s quality of life and offer ways for businesses to implement their solutions. Through rapid advances in the quality of sensors, new methods emerged, combining different types of devices to create a better picture of the environment. The purpose of this dissertation is to provide useful information thought public services, that can be accessed by people visiting or residing in the beach area of Costa Nova and Barra. It also provides a solution for the traffic classification problem that projects based on radar data tend to face. These applications take advantage of the devices implemented in the PASMO project, such as parking sensors, radars, and CCTV cameras. By making the service public, businesses have the opportunity to build applications on top of it, utilizing the sensor data without being directly connected to the data storage. The example developed in this dissertation offers a dashboard experience where users can navigate through charts that provide a variety of data and real-time maps. It also provides a public API that researchers and businesses can use to develop new applications in the context of PASMO. The other area tackled in this document is traffic classification. Although the data provided is reliable for the most part, one big issue is the accuracy of vehicle classification provided by the radar. Still, this device offers precise values when it comes to detection, with the cameras doing a good job in classifying traffic. The goal is to combine these two devices to present much precise information, using state-of-the-art object detection algorithms and sensor fusion methods. In the end, the system will enrich the PASMO project by making its data easily available to the public while correcting the accuracy problems of some devices. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-05-17T13:07:57Z 2021-02-25T00:00:00Z 2021-02-25 |
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info:eu-repo/semantics/publishedVersion |
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http://hdl.handle.net/10773/31381 |
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eng |
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eng |
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openAccess |
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