Fuzzy logic has emerged as a powerful tool for handling uncertainty and imprecision in various domains, and its application in the Internet of Things (IoT) domain has gained significant attention in recent years. This abstract provides a comprehensive overview of the applications of fuzzy logic in IoT systems. The IoT paradigm involves the interconnection of numerous devices and sensors, leading to vast amounts of heterogeneous data streams. Fuzzy logic offers a flexible and intuitive framework for processing and interpreting this data, enabling more intelligent decision-making in IoT applications. One of the key areas where fuzzy logic finds application in IoT is in sensor data fusion and interpretation. By incorporating fuzzy inference systems, IoT devices can effectively deal with ambiguous and noisy sensor data, leading to more accurate and reliable insights. Fuzzy logic-based control systems also play a vital role in IoT-enabled smart environments, facilitating adaptive and context-aware behaviour in interconnected devices. Furthermore, fuzzy logic enables the development of personalized and adaptive IoT services by modelling user preferences and context information. This facilitates the creation of intelligent IoT systems that can adapt their behaviour dynamically based on changing environmental conditions and user requirements. Moreover, fuzzy logic contributes to IoT security and privacy by providing robust mechanisms for anomaly detection and intrusion prevention. By leveraging fuzzy inference techniques, IoT systems can identify abnormal behaviour and mitigate potential security threats effectively. In summary, the integration of fuzzy logic techniques with IoT systems offers a promising avenue for addressing the inherent complexities and uncertainties in IoT environments. This abstract highlight the diverse applications of fuzzy logic in IoT, ranging from sensor data fusion to adaptive control and security, underscoring its significance in advancing the capabilities and resilience of IoT ecosystems.