AIoT's Impact on Sustainable Development: A Bibliometric Analysis

In an article published in the journal Sensors, researchers explored the pivotal role of artificial intelligence of things (AIoT) in realizing sustainable development goals (SDGs). Conducting a comprehensive bibliometric analysis from 1989 to 2022 using 9182 documents from Scopus and Web of Science (WoS), the study identified AIoT as a key player in creating efficient, data-driven, and autonomous Internet of things (IoT) systems.

Study: AIoT
Study: AIoT's Impact on Sustainable Development: A Bibliometric Analysis. Image credit: metamorworks/Shutterstock


The achievement of the SDGs, set by the United Nations (UN), is crucial for global well-being and environmental sustainability. These 17 goals with 169 targets encompass a comprehensive approach to societal, economic, and environmental development. To successfully implement SDG measures, interlinkages among sectors, societal actors, and countries must be considered, necessitating appropriate conceptual frameworks and technological integration.

While prior studies have recognized the influence of AI and blockchain in technology and society, and highlighted IoT's role in SDG fulfilment, a novel field called AIoT is gaining prominence. AIoT integrates AI with IoT, forming autonomous systems employing AI algorithms for environmental interaction, data analysis, and real-time decision-making. Despite AIoT's potential for optimizing processes and addressing societal and environmental challenges, there's a lack of systematic studies detailing its current status, evolution, and application in achieving SDGs.

This research aimed to bridge this gap through a comprehensive bibliometric analysis covering 9182 documents from 1989 to 2022. The authors explored the current state of AIoT in realizing SDGs and identified key authors, articles, topics, and research directions.


This research employed a robust bibliometric analysis to investigate the evolving landscape of AI, IoT, and AIoT in the context of achieving SDGs. Utilizing the established methodologies, the study leveraged Scopus and WoS databases for their accuracy and relevance in bibliometric studies.

The R package "Bibliometrics" facilitated the analysis, covering 12,675 documents from 1989 to 2022. After eliminating duplicates and applying inclusion criteria focused on AI, IoT, and/or AIoT with a specific emphasis on SDGs, 9182 documents underwent meticulous examination. The research was structured into six categories, encompassing main information, citations, sources, authors, countries, and documents, providing a comprehensive overview.

The technical process involved a systematic four-stage approach: initial search for topics, keywords, and data sources; data identification, exportation, preprocessing, and import to Bibliometrix; bibliometric analysis and scientific mapping; and result interpretation and conclusions. The study's meticulous methodology sheds light on key authors, influential articles, and emerging research directions, offering a nuanced understanding of the synergy between AI, IoT, and AIoT in pursuing SDGs.

Results Analysis

The research findings provided a comprehensive overview of the bibliometric and scientific mapping study on the intersection of AI, IoT, and SDGs. The study analyzed 9,182 documents published from 1989 to 2022 across various sources, revealing key trends and insights. In terms of the main information, the average document age was 4.07 years, with a significant annual growth rate of 26.34% from 1989 to 2022. Most documents (3,955) were published as conference papers, emphasizing the dynamic nature of the field.

The citations section highlighted the increasing relevance of AI, IoT, and sustainability, with a positive annual growth rate in published documents and average citations per year. The document co-citation network demonstrated the interdisciplinary nature of the topic, with six main clusters indicating diverse perspectives and contributions. Analyzing the sources, the study identified 3,641 sources, with "Sustainability" leading in the number of published documents. "Journal of Cleaner Production," "Sustainable Cities and Society," and "Sensors" emerged as impactful sources based on h-index and total citations.

The authors' analysis showcased a multidisciplinary collaboration, with top authors like Liu Y., Wang X., and Wang J. leading the publication trends since around 2009. Lotka's law revealed that the majority of authors participated in a single document.
Examining the global contribution, authors from 117 countries contributed to the publications, with China, the USA, India, Italy, and the UK leading in document count. The collaboration network map emphasized the global significance of the topic.

The study delved into the evolving thematic landscape, uncovering key aspects like the influence of AI in decision support, the incorporation of IoT in smart cities, human factors, and the utilization of AI and IoT in manufacturing and energy sectors. This analysis clearly illustrated the dynamic trends, offering a nuanced perspective on how AI and IoT contribute across varied sectors over time. The thematic evolution analysis highlighted a shift towards sustainability, with a profound focus on SDGs emerging after 2014.


This discussion encapsulated the critical role of innovative technologies, including AI, IoT, and AIoT, in advancing SDGs by 2030. The study analyzed 9,182 documents from 1989 to 2022 and unveiled a growing scientific interest, particularly since 2018. Key findings included an annual growth rate of 26.34%, an average document age of 4.07 years, and an increasing average of citations per year. Top impactful sources included "Journal of Cleaner Production" and "Sustainability," with prolific authors like Liu Y. and Wang X. driving research trends. Countries like China, the USA, and India led in document count and citations. The study identified influential documents and prevalent keywords, emphasizing the evolving thematic focus on sustainable development, AI, and IoT.


In conclusion, this comprehensive bibliometric analysis underscored the pivotal role of AIoT in advancing sustainable development goals. The research, spanning 1989 to 2022, revealed a surge in scientific interest, emphasizing the dynamic nature of the field. With notable contributions from prolific authors and global collaboration, the study illuminated key trends, influential sources, and evolving thematic focuses, providing a nuanced understanding of the intersection between cutting-edge technologies and sustainable development objectives. This research contributed significantly to the scholarly discourse, guiding future endeavors in harnessing AIoT for global sustainability.

Journal reference:
Soham Nandi

Written by

Soham Nandi

Soham Nandi is a technical writer based in Memari, India. His academic background is in Computer Science Engineering, specializing in Artificial Intelligence and Machine learning. He has extensive experience in Data Analytics, Machine Learning, and Python. He has worked on group projects that required the implementation of Computer Vision, Image Classification, and App Development.


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