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A Crowdsensing Platform for Monitoring of Vehicular Emissions: A Smart City Perspective

Author

Listed:
  • Marianne Silva

    (Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil)

  • Gabriel Signoretti

    (Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil)

  • Julio Oliveira

    (Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil)

  • Ivanovitch Silva

    (Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil
    Digital Metropolis Institute, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil)

  • Daniel G. Costa

    (Department of Technology, State University of Feira de Santana, Feira de Santana 44036-900, Brazil)

Abstract

Historically, cities follow reactive planning models where managers make decisions as problems occur. On the other hand, the exponential growth of Information and Communication Technologies (ICT) has allowed the connection of a diverse array of sensors, devices, systems, and objects. These objects can then generate data that can be transformed into information and used in a more efficient urban planning paradigm, one that allows decisions to be made before the occurrence of problems and emergencies. Therefore, this article aims to propose a platform capable of estimating the amount of carbon dioxide based on sensor readings in vehicles, indirectly contributing to a more proactive city planning based on the monitoring of vehicular pollution. Crowdsensing techniques and an On-Board Diagnostic (OBD-II) reader are used to extract data from vehicles in real time, which are then stored locally on the devices used to perform data collection. With the performed experiments, it was possible to extract information about the operation of the vehicles and their dynamics when moving in a city, providing valuable information that can support auxiliary tools for the management of urban centers.

Suggested Citation

  • Marianne Silva & Gabriel Signoretti & Julio Oliveira & Ivanovitch Silva & Daniel G. Costa, 2019. "A Crowdsensing Platform for Monitoring of Vehicular Emissions: A Smart City Perspective," Future Internet, MDPI, vol. 11(1), pages 1-20, January.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:1:p:13-:d:195705
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    References listed on IDEAS

    as
    1. N. Komninos & C. Kakderi & A. Panori & P. Tsarchopoulos, 2019. "Smart City Planning from an Evolutionary Perspective," Journal of Urban Technology, Taylor & Francis Journals, vol. 26(2), pages 3-20, April.
    2. Kellyton dos Santos Brito & Marcos Antônio da Silva Costa & Vinicius Cardoso Garcia & Silvio Romero de Lemos Meira, 2015. "Is Brazilian Open Government Data Actually Open Data?: An Analysis of the Current Scenario," International Journal of E-Planning Research (IJEPR), IGI Global, vol. 4(2), pages 57-73, April.
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    Cited by:

    1. Mihui Kim & Junhyeok Yun, 2020. "Development of User-Participatory Crowdsensing System for Improved Privacy Preservation," Future Internet, MDPI, vol. 12(3), pages 1-19, March.
    2. Giovanni Pau & Alessandro Severino & Antonino Canale, 2019. "Special Issue “New Perspectives in Intelligent Transportation Systems and Mobile Communications towards a Smart Cities Context”," Future Internet, MDPI, vol. 11(11), pages 1-3, October.
    3. Isam Mashhour Al Jawarneh & Luca Foschini & Paolo Bellavista, 2023. "Efficient Integration of Heterogeneous Mobility-Pollution Big Data for Joint Analytics at Scale with QoS Guarantees," Future Internet, MDPI, vol. 15(8), pages 1-28, August.

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