Implementation of cloud server utilised transmission line fault detection and analysis using artificial neutral network based model

This work proposes an AI-IOT based transmission line fault detection comprising cloud server and artificial neural network. In this proposed work, current sensing panel along with Arduino panel are incorporated to capture the data from the transmission line and sent to central control system using WiFi module. Additionally, this topology enables real-time data transmission, enabling continuous monitoring of device faults from any remote location by server or application. However, the faulty and non-faulty data (in terms of current) are further trained using artificial neural network-based model; so that any data which are captured through IoT network can be directly analysed to predict whether it is faulty or not. Thus, a compact IoT cloud server-based system with minimal hardware requirement can be designed with incorporation of ANN model. The performance has been shown in terms of data received via Arduino, as well as IoT cloud server. Finally, performance analysis in terms of fault detection accuracy and computation time has been presented to justify the superiority of the proposed network compared with the existing works available in the literature.