The Internet of Things (IoT), as a key technology of the digital transformation era, has experienced rapid growth, increasing the need to identify its emerging trends for researchers, policymakers, and technology managers. This study aims to identify emerging trends in IoT technology based on patent data analysis and artificial intelligence (AI) methods, particularly text mining. This applied study was conducted using a descriptive-analytical approach and a data science methodology. The required data were extracted from the global patent database Lens and, after preprocessing, active IoT-related patents were analyzed. To identify technological trends, International Patent Classification (IPC) analysis, text mining of patent titles, and frequency analysis of keywords and applications were employed. The results showed a significant increase in IoT-related patent activity in recent years, with Samsung, IBM, Qualcomm, Intel, LG, and Cisco identified as major players. IPC analysis indicated that innovations primarily focus on wireless communications, network management, information security, and data processing. Text-mining findings revealed that smart living, smart industry and manufacturing, and smart monitoring are among the major emerging IoT trends. Furthermore, autonomous vehicles, smart factories, and things as customers were identified as major applications of this technology. The findings can support technology policymaking, research and development planning, and technology foresight in digital technologies.