Due to over voltage, overheating, or some adverse environmental conditions, fatigueness may arise in the insulation present in the induction motors that are very common electrical appliances used in various industries. This fatigueness is one of the key factors to induce various faults in an induction motor that can create a devastating situation in the industry. Hence detection of the fault at its early stage is very much desirable in the industry. In the present scenario motor data are readout through some DAS, and then an analysis of the collected data is done in offline mode which is not an acceptable fault detection technique. Here we have developed a fault detection system that captures and analyzes the data using Park’s Vector Approach in online mode without sacrificing in terms of accuracy compared to the state-of-the-art offline techniques. The proposed system is developed on system-on-chip (SoC) platform which is a hybrid platform of CPU and field programmable gate array (FPGA). This SoC-based hybrid platform provides hardware software codesign which not only makes the system flexible but also reduces the detection latency compared to its only software solution.