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Assessment and Optimization of Air Monitoring Network for Smart Cities with Multicriteria Decision Analysis

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Intelligent Information and Database Systems (ACIIDS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10192))

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Abstract

Environmental monitoring networks need to be designed in efficient way, to minimize costs and maximize the information granted by their operation. Gathering data from monitoring stations is also the essence of Smart Cities. Agency of Regional Air Quality Monitoring in the Gdańsk Metropolitan Area (pol. ARMAAG) was assessed in terms of its efficiency to obtain variety of information. The results on one-month average concentrations of seven parameters (data for three years) for eight monitoring stations were the input data to multicriteria decision analysis assessment and the least effective was detected.

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Authors and Affiliations

  1. Department of Management, Faculty of Management and Economics, Gdańsk University of Technology, 11/12 G. Narutowicza St., 80-233, Gdańsk, Poland

    Aleksander Orłowski

  2. Department of Analytical Chemistry, Chemical Faculty, Gdańsk University of Technology, 11/12 G. Narutowicza St., 80-233, Gdańsk, Poland

    Mariusz Marć, Jacek Namieśnik & Marek Tobiszewski

Authors
  1. Aleksander Orłowski
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  2. Mariusz Marć
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  3. Jacek Namieśnik
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  4. Marek Tobiszewski
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Corresponding author

Correspondence to Aleksander Orłowski .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Satoshi Tojo

  3. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Le Minh Nguyen

  4. Wrocław University of Science and Technology, Wroclaw, Poland

    Bogdan Trawiński

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Orłowski, A., Marć, M., Namieśnik, J., Tobiszewski, M. (2017). Assessment and Optimization of Air Monitoring Network for Smart Cities with Multicriteria Decision Analysis. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10192. Springer, Cham. https://doi.org/10.1007/978-3-319-54430-4_51

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  • DOI: https://doi.org/10.1007/978-3-319-54430-4_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54429-8

  • Online ISBN: 978-3-319-54430-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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