Internet of Things (IoT) invoke to linkage of individually identifiable embedded devices within the current internet infrastructure. Wireless Sensor Network (WSN) is a network containing self-ruling sensors, which monitors environmental conditions. Interconnection of these sensors into IoT will be a big revolution in growing sensor technology. The increase in the number of sensor nodes, increases the number of faulty nodes. This affects the Quality of Service (QoS) of WSN based IoT. Efficient detection and reuse of faulty nodes enhances the quality of monitoring to a large extend. Due to the difficulty in indentifying the internal status of sensor nodes, it is important to develop algorithms to find faulty nodes. The conventional fault detection algorithms face low detection accuracy. In this work, three input fuzzy inference system (FIS) is used, which identifies hardware faults like, transmitter circuit condition, receiver circuit condition and battery condition. The simulation results show that the proposed scheme increases the detection accuracy when compared to the conventional schemes. © 2017 IEEE.