Defining data-driven analytical methods on improving energy-efficiency in apartment buildings

Abstract

Energy efficiency is one of the key characteristics of smart cities and data-driven analytical methods, especially including Internet of Things (IoT) sensors, and meaningful indicators are provided to support initiatives but also changing behavior at the citizen level. The analysis is often undertaken in closed systems that contain sensors, data acquisition, analysis and visualization. To improve the effectiveness of energy-efficiency initiatives in climate programs, harmonization of analytical methods and quality assurance of the data are required. This paper provides an overview of these themes based on the findings from two European Union (EU)-funded projects, European Regional Development Fund (ERDF) 6Aika Climate Friendly Housing Companies and Horizon 2020 mySMARTLife.