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Perishable Products: Enhancing Delivery Time Efficiency with Big Data, AI, and IoT

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Data Intelligence and Cognitive Informatics (ICDICI 2023)

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

This article highlights the significant advancements that can be achieved by implementing Big Data (BD), Artificial Intelligence (AI), and the Internet of Things (IoT) in transporting delicate and sensitive products, with a specific focus on reducing delivery time (DT). Through a thorough study conducted over a defined period, we assess the outcomes of incorporating innovative BD, AI, and IoT technologies to diminish delivery delays and enhance punctual arrivals at designated destinations. Our findings indicate that utilizing these three technologies can remarkably improve delivery delays, surpassing 6%, 11%, and 13% for BD, AI, and IoT, respectively, compared to conventional transport (CT), while ensuring the utmost security measures. Furthermore, by achieving perfect synchronization of the arrival and departure of different means of transport, the overall efficiency and reliability of the transportation process are significantly enhanced.

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Author information

Authors and Affiliations

  1. Higher School of Technology, Guelmim, Ibn Zohr University Agadir, Agadir, Morocco

    Saâdia Chabel

  2. Abdelmalek Essaâdi University, Tetouan, Morocco

    El Miloud Ar-Reyouchi

Authors
  1. Saâdia Chabel
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  2. El Miloud Ar-Reyouchi
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Corresponding author

Correspondence to El Miloud Ar-Reyouchi .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, GITAM University, Bangalore, Karnataka, India

    I. Jeena Jacob

  2. ISOM Department, University of Florida, Gainesville, FL, USA

    Selwyn Piramuthu

  3. Gdańsk University of Technology, Gdańsk, Poland

    Przemyslaw Falkowski-Gilski

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Chabel, S., Ar-Reyouchi, E.M. (2024). Perishable Products: Enhancing Delivery Time Efficiency with Big Data, AI, and IoT. In: Jacob, I.J., Piramuthu, S., Falkowski-Gilski, P. (eds) Data Intelligence and Cognitive Informatics. ICDICI 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-7962-2_21

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