A Clustering Technique to Detect the Abnormal Voltage using Sensors

In order to resolve the issue of abnormal voltage of household appliances and electrocution, real-time monitoring, conditional awareness to detect abnormal voltage situations in households and assuring the safety and reliability of household electrical mechanism among the increasing need for electricity is leading principle. It is necessary to check the abnormal conditions in the households to avoid the losses. Abnormal voltage conditions, such as overvoltage and undervoltage can rise to power quality issues which leads to the appliances damage due to load fluctuations, faults etc. Transformers are present in the society but they don’t guarantee the accurate conversion of high and low voltage to normal voltage. One of the major challenges labelled is the possible effect on households located near industrial areas, where shared transformers may lead to voltage fluctuations. It is too much important to have real-time monitoring and situational awareness to respond against the abnormal voltage conditions. This study proposes a novel approach utilizing IoT sensors with K means algorithm for collecting the real-time data on voltage levels in households leading to system break of circuit and alerting through the help of help of alarm providing a safe and secured environment in the households and in the society