Monitoring and Controlling of Energy Consumption using IOT-based Predictive Maintenance

The need for monitoring and controlling of Energy consumption raised due to the fact that residential units and at home electrical devices have witnessed a significant hike in the electrical consumption and hence excess electricity bills due to negligent usage of worn-out electrical appliances consuming a lot of power. Also, these devices release a lot of heat, vibration, chemicals and residential pollutants into the air, which accounts to significant global warming, climatic hazards, etc. In today’s day and age where world is witnessing the ever increasing need for research into the field of IoT, the role of IoT-based predictive maintenance takes the premier lead as it is responsible for generating the dataset. The algorithm developed for simulating the probability of success or failure of the electrical home device is the SVM algorithm via a few parameters fitting the dataset. It will help predict the reliability and sustainability of the electrical device put up in use at homes. HEMS enhances the customer-interaction and control over the device even, keeping the customer well-updated with the power consumed via GUI-based client application interface. In this paper, we also gain insight into the relationship of the hardware and software specifications involved in the Home Energy Management System (HEMS).