The Internet of Things is revolutionizing how in-terconnected devices communicate and interact within several applications, ranging from health monitoring to smart city development. Yet, the data management in these systems is challenged by imprecision and noise inherent in Internet of Things environments. Fuzzy Rule-Based Systems have emerged as a solution, aptly handling the uncertainty and complexity in decision-making processes these environments present. However, current Fuzzy Rule-Based Systems implementations in Internet of Things often face limitations due to their ad-hoc nature and heavy reliance on specific hardware, thereby restricting their application in diverse and evolving Internet of Things infrastructures. In response to these challenges, we present JFML-IoT, an innovative open-source library that bridges the gap between Fuzzy Rule-Based Systems and Internet of Things devices. JFML-IoT extends the JFML library, implementing the IEEE Std 1855-2016 for Fuzzy Markup Language and adapting its capabilities to the unique demands of the Internet of Things paradigm. This library not only facilitates remote Fuzzy Rule-Based Systems deployment but also excels in generating source code for Internet of Things microcontrollers, thus enabling a new level of hardware abstraction and versatility. Our approach significantly enhances the scalability, flexibility, and integration of Fuzzy Rule-Based Systems within varied Internet of Things systems. To demonstrate the practical application and effectiveness of JFML-IoT, we conducted a case study in a real-world environment. This case study showcases how JFML-IoT can improve data management in Internet of Things systems, offering scalable, efficient, and adaptable solutions that are critical in modern Internet of Things applications.