The chapter introduces a new IoT system that uses fuzzy AI with blockchain to improve IoT security. IoT is becoming important to many industries, and the need to protect devices and data is greater than ever. The approach uses fuzzy logic to detect different kinds of security threats that occur in real-world IoT setups. Blockchain supports this by securing data and making transactions tamper-proof. The system works as a fuzzy AI decision engine that is always on the lookout. It sorts through complex security data. Then it responds even when the signals are unclear. It is not flawless, and mistakes still happen. Yet it keeps learning and adapting in real time. This makes it resilient against ongoing risks. The chapter explains the methods used to design this system. It also gives experimental results with proof of how effective it is at protecting IoT devices and networks. Using fuzzy AI with blockchain is not a theoretical idea. It increases the safety of devices and ensures that information remains reliable. This mix creates a firm base for future IoT applications that will demand trust and resilience. There are still challenges. Fuzzy AI can falter when the input is incomplete or highly uncertain. But blockchain makes the system stronger with its immutable records and secure protocols. The combination is a difficult match to break. It fits industrial and business environments where IoT security cannot reduce system performance. This model gives answers to that need. The result is a model that improves defences against cyber threats. It improves IoT security and makes networks safer and more intelligent. This study is important because the connected world requires systems that can be trusted. Using fuzzy AI with blockchain gives reliable and secure IoT solutions that industries can depend on.