The Inverter Fault Diagnosis dataset is a comprehensive collection of data aimed at facilitating research and development in the field of fault diagnosis for solar integrated grid-side three-phase inverters. This dataset includes three key features, namely Ea, Eb, and Ec, representing the energy calculated from the fault currents for phases A, B, and C, respectively.
The ability of detecting human postures is particularly important in several fields like ambient intelligence, surveillance, elderly care, and human-machine interaction. Most of the earlier works in this area are based on computer vision. However, mostly these works are limited in providing real time solution for the detection activities. Therefore, we are currently working toward the Internet of Things (IoT) based solution for the human posture recognition.