Development of Intelligent Internet of Things Systems for Real-Time Data Processing and Decision Making

This research aims to study and develop an intelligent Internet of Things (IoT) system that is capable of real-time data processing and supports information-based decision-making. Using a qualitative approach through literature study and library research methods, this study analyzes various scientific references and technical documents related to IoT technology, artificial intelligence (AI), edge computing, and decision support systems. The results show that the integration between IoT devices and artificial intelligence algorithms allows the system to not only collect and send data, but also process and analyze data directly on-site to provide a fast and adaptive response. These smart systems are very relevant to be applied in various fields such as manufacturing, healthcare, transportation, and smart city industries. The research also identified the main challenges faced in the development of these systems, such as the limitations of computing power on edge devices, data security, interoperability between devices, and the need for communication protocol standards. These findings provide a solid conceptual basis for the development of efficient, responsive, and highly usable intelligent IoT systems to support real-time decision-making. Further research is recommended to examine practical implementation and case studies to test the effectiveness of the system directly.