Malfunction and Bad Behavior Diagnosis on Domestic Environment

Abstract Greenhouse gas emissions from homes arise primarily from fossil fuels burned for heat, the use of products that contain greenhouse gases, and the handling of waste. Human activities are responsible for almost all of the increase in greenhouse gases in the atmosphere over the last 150 years. The household sector is one of the biggest aggregate consumers and this is the reason why increasingly policies have been considering it. One of the key factors in curbing energy consumption in this sector is widely recognized to be due to erroneous behaviors and systems malfunctioning, mainly explained by the lack of awareness of the final user; so, training the final user to energy awareness can be more effective and cheaper than other policies. In this context, energy management in homes is playing, and will play even more in future, a key role in increasing the final consumer awareness towards its own energy consumption and consequently in bursting its active role in smart grids. The aim of this paper is to highlight the economic benefits of low cost intelligent control domestic devices, to identify energy behavior, system status and improve energy efficiency. The scope is to develop interaction between final users to create a network of energy consumption efficiency. The paper presents an application of Multi-scale Principal Component Analysis to diagnose inefficient occupant behavior and systems malfunctioning and suggest good practices of energy conservation