The Sustainable Development of Industrial Production by Internet of Things Technology: Based on Bibliometric Analysis Methods

Internet of Things (IoT) technology is crucial for advancing sustainable development in industrial production. This study employs bibliometric methods, utilizing tools such as CiteSpace, VOSviewer, and Bibliometrix, to conduct a systematic analysis of 1,047 relevant publications from the Web of Science Core Collection between 2012 and 2025. The aim is to map the knowledge structure, research theme evolution, and future development pathways within this field. Findings indicate the field's development unfolds in two distinct phases: an exploratory period (2012–2018) and a developmental phase (2019–2025). Research focus has shifted from early-stage energy efficiency improvements and environmental monitoring toward intelligent manufacturing systems and their integration with cutting-edge technologies such as artificial intelligence, big data, and digital twins. Core research themes encompass the Industrial Internet of Things (IIoT), blockchain technology, and industrial environmental and lifecycle management. Keyword co- occurrence analysis identified three major research clusters: 1) Technology-Support Cluster featuring IIoT, block- chain, 5G, and cloud computing; 2) Value Strategy Cluster focusing on life cycle assessment, circular economy, and supply chain management; 3) New Technology Intervention Cluster involving artificial intelligence and Industry 5.0. Furthermore, citation analysis reveals that current research frontiers concentrate on implementing circular economy strategies, yet face multiple challenges including data interoperability, high system integration costs, and cybersecurity. This study employs systematic bibliometric analysis for the first time to clearly delineate the knowledge landscape of IoT-driven industrial sustainability. It identifies two evolutionary stages in this field—from exploration to development—and highlights research clusters centered on industrial IoT, blockchain, and lifecycle management. The findings provide scholars, industry practitioners, and policymakers with an objective research panorama and development roadmap, pointing to key future research directions such as technology convergence, data interoperability, and economic viability. Subsequent research should focus on addressing these challenges and exploring synergies between IoT, artificial intelligence, and sustainable development practices to foster more resilient industrial growth.