On the Design of Vehicular Virtual Sensors

Campolina, Andre B.; Rettore, Paulo H. L.; Machado, Max do Val; Loureiro, Antônio A. F.

doi:10.1109/dcoss.2017.21

Cited by 7 publications

(4 citation statements)

References 24 publications

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“…Luxury car manufacturers and sellers continually collect diverse information from various sources, including sophisticated sensors within vehicles [92], complex customer interactions, and dynamic environmental data. However, these data hold significance beyond enhancing internal operations and improving customer experiences.…”

Section: Unlocking Intrinsic Value Through Data Monetizationmentioning

confidence: 99%

Luxury Car Data Analysis: A Literature Review

Barakati,

Bertini,

Corsi

et al. 2024

Data

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The concept of luxury, considering it a rare and exclusive attribute, is evolving due to technological advances and the increasing influence of consumers in the market. Luxury cars have always symbolized wealth, social status, and sophistication. Recently, as technology progresses, the ability and interest to gather, store, and analyze data from these elegant vehicles has also increased. In recent years, the analysis of luxury car data has emerged as a significant area of research, highlighting researchers’ exploration of various aspects that may differentiate luxury cars from ordinary ones. For instance, researchers study factors such as economic impact, technological advancements, customer preferences and demographics, environmental implications, brand reputation, security, and performance. Although the percentage of individuals purchasing luxury cars is lower than that of ordinary cars, the significance of analyzing luxury car data lies in its impact on various aspects of the automotive industry and society. This literature review aims to provide an overview of the current state of the art in luxury car data analysis.

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Section: Unlocking Intrinsic Value Through Data Monetizationmentioning

confidence: 99%

Luxury Car Data Analysis: A Literature Review

Barakati,

Bertini,

Corsi

et al. 2024

Data

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“…To develop ITS applications, significant data is required from real or virtual sensors [5]. Vitor et al [4] present a platform to collect, process, and export heterogeneous data from smart city sensors, providing different statistics and visualizations.…”

Section: A Data Collection and Fusionmentioning

confidence: 99%

DataFITS: A Heterogeneous Data Fusion Framework for Traffic and Incident Prediction

Zißner,

Rettore,

Santos

et al. 2023

IEEE Trans. Intell. Transport. Syst.

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This paper introduces DataFITS (Data Fusion on Intelligent Transportation System), an open-source framework that collects and fuses traffic-related data from various sources, creating a comprehensive dataset. We hypothesize that a heterogeneous data fusion framework can enhance information coverage and quality for traffic models, increasing the efficiency and reliability of Intelligent Transportation System (ITS) applications. Our hypothesis was verified through two applications that utilized traffic estimation and incident classification models. DataFITS collected four data types from seven sources over nine months and fused them in a spatiotemporal domain. Traffic estimation models used descriptive statistics and polynomial regression, while incident classification employed the k-nearest neighbors (k-NN) algorithm with Dynamic Time Warping (DTW) and Wasserstein metric as distance measures. Results indicate that DataFITS significantly increased road coverage by 137% and improved information quality for up to 40% of all roads through data fusion. Traffic estimation achieved an R 2 score of 0.91 using a polynomial regression model, while incident classification achieved 90% accuracy on binary tasks (incident or non-incident) and around 80% on classifying three different types of incidents (accident, congestion, and non-incident).

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“…Já em [Campolina et al 2017], os autores investigam a aplicac ¸ão de sensores virtuais em veículos para identificac ¸ão do comportamento do motorista e identificac ¸ão do motorista. Esse trabalho utiliza meios de medic ¸ão física já presentes nos veículos e sensores também presentes nos celulares.…”

Section: Trabalhos Relacionadosunclassified

“…Caso de utilizac ¸ão Dados obtidos em [Zaidan et al 2020] Low-Cost-Sensor Helsinki [Campolina et al 2017…”

Section: Artigounclassified

Análise de Poluição Atmosférica Utilizando Modelos de Sensoriamento Virtual

Campos

Villas

2021

Anais Do v Workshop De Computação Urbana (CoUrb 2021)

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Modelos de sensoriamento virtuais têm sido utilizados para gerar dados sintéticos e fornecer informações complementares. Essa abordagem é importante para analisar aspectos para os quais não existem sensores físicos. Alguns dos problemas na literatura em análise de poluição atmosférica estão ligados à dificuldade financeira para a compra de sensores, à perda de informação e ao armazenamento de dados inválidos. Portanto, esse artigo analisa diversos fatores que contribuem para a poluição atmosférica e apresenta a comparação de diferentes modelos para criação de um sensor virtual para o monóxido de carbono. Por fim, o modelo de Boosted Trees produziu os melhores resultados, com média de 5.078 de RMSE, na geração dos dados sintéticos de cada cidade analisada.

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On the Design of Vehicular Virtual Sensors

Cited by 7 publications

References 24 publications

Luxury Car Data Analysis: A Literature Review

Luxury Car Data Analysis: A Literature Review

DataFITS: A Heterogeneous Data Fusion Framework for Traffic and Incident Prediction

Análise de Poluição Atmosférica Utilizando Modelos de Sensoriamento Virtual

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