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A bibliometric exploration of deep learning application in sustainable smart cities and agriculture

Research output: Contribution to journalConference articlepeer-review

Abstract

The pursuit of secure, resilient, and livable cities by humanity has led to the investigation of using computational tools in the creation and advancement of sustainable smart cities and smart agriculture. Therefore, the utilization of artificial intelligence in sustainable smart cities and smart agriculture (DLSSCA) has emerged as a significant area of study, resulting in a multitude of papers, citations, and collaborations. Nevertheless, there is a dearth of articles that examine the trends in publications and the research landscape in the field of DLSSCA research. This report analyzes the present state and future prospects of DLSSCA research. The PRISMA methodology was employed to systematically locate, screen, and analyze a total of 462 publications on DLSSCA research from the Scopus database spanning the period between 2017 and 2023. The findings indicated a significant increase in the number of publications, from 4 to 65, and citations, from 3 to 1,259. This demonstrates the considerable social influence and research enthusiasm among stakeholders. The productivity was ascribed to the alignment with national interests, research agendas, and the availability of national and international funding. Subsequent investigations will probably prioritize the examination of the socio-economic, ethical, policy, and technical dimensions of the subject matter. Given its increasing significance, it is anticipated that there will be a continued upward trend in worldwide scientific pursuits, publications, citations, and products and services.

Original languageEnglish
Article number020025
JournalAIP Conference Proceedings
Volume3260
Issue number1
DOIs
StatePublished - 22 Jul 2025
Event6th International Conference on Computational Intelligence and Digital Technology, ICCIDT2K 2024 - Kottayam, India
Duration: 3 May 20244 May 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  3. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • artificial intelligence
  • bibliometric analysis
  • deep learning
  • machine learning
  • sustainable smart agriculture
  • sustainable smart city

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