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An Innovative Industry 4.0 Cloud Data Transfer Method for an Automated Waste Collection System

Author

Listed:
  • Costel Emil Cotet

    (Faculty of Industrial Engineering and Robotics, Department of Robots and Manufacturing Systems, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Gicu Calin Deac

    (Faculty of Industrial Engineering and Robotics, Department of Robots and Manufacturing Systems, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Crina Narcisa Deac

    (Faculty of Industrial Engineering and Robotics, Department of Robots and Manufacturing Systems, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Cicerone Laurentiu Popa

    (Faculty of Industrial Engineering and Robotics, Department of Robots and Manufacturing Systems, University Politehnica of Bucharest, 060042 Bucharest, Romania)

Abstract

Moving to Industry 4.0 involves the collection of massive amounts of data and the development of big data applications that can ensure a quick data flow between different systems, including massive amounts of data and information collection from smart sensors, and sending them to cloud applications that allow real-time data monitoring and processing. Securing and protecting the transmitted data represents a big issue to be discussed and resolved. In the paper, we propose a new method of data encoding and encryption for cloud applications using PNG format images. The proposed method is described in comparison with one of the classical methods of data encoding and transmission used currently. The paper includes a case study in which the proposed method was used to collect and transmit data from an automated waste collection system. The results show that the proposed method represents a secure, fast and efficient way to send and store the data in the cloud compared to the methods currently used. The proposed method is not limited to being used only in waste management but can be used successfully for any type of manufacturing system from smart factories.

Suggested Citation

  • Costel Emil Cotet & Gicu Calin Deac & Crina Narcisa Deac & Cicerone Laurentiu Popa, 2020. "An Innovative Industry 4.0 Cloud Data Transfer Method for an Automated Waste Collection System," Sustainability, MDPI, vol. 12(5), pages 1-15, February.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:1839-:d:326515
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    References listed on IDEAS

    as
    1. Cicerone Laurentiu Popa & George Carutasu & Costel Emil Cotet & Nicoleta Luminita Carutasu & Tiberiu Dobrescu, 2017. "Smart City Platform Development for an Automated Waste Collection System," Sustainability, MDPI, vol. 9(11), pages 1-15, November.
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    Cited by:

    1. Atiq Zaman, 2022. "Waste Management 4.0: An Application of a Machine Learning Model to Identify and Measure Household Waste Contamination—A Case Study in Australia," Sustainability, MDPI, vol. 14(5), pages 1-18, March.
    2. Chowdhury, Naimur Rahman & Paul, Sanjoy Kumar & Sarker, Tapan & Shi, Yangyan, 2023. "Implementing smart waste management system for a sustainable circular economy in the textile industry," International Journal of Production Economics, Elsevier, vol. 262(C).
    3. Yan Wang & Congxianzi Pei & Qiushuo Li & Jingbang Li & Deng Pan & Ciwei Gao, 2020. "Flow Shop Providing Frequency Regulation Service in Electricity Market," Energies, MDPI, vol. 13(7), pages 1-15, April.

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