*Article* **A Platform for Analysing Huge Amounts of Data from Households, Photovoltaics, and Electrical Vehicles: From Data to Information**

**Antonio Cano-Ortega 1,\*, Miguel A. García-Cumbreras 2, Francisco Sánchez-Sutil <sup>1</sup> and Jesús C. Hernández <sup>1</sup>**

<sup>1</sup> Department of Electrical Engineering, Spain University of Jaen, 23071 Jaén, Spain

<sup>2</sup> Department of Computer Engineering, Spain University of Jaen, 23071 Jaén, Spain

**\*** Correspondence: acano@ujaen.es; Tel.: +34-953-21-23-43

**Abstract:** Analytics is an essential procedure to acquire knowledge and support applications for determining electricity consumption in smart homes. Electricity variables measured by the smart meter (SM) produce a significant amount of data on consumers, making the data sets very sizable and the analytics complex. Data mining and emerging cloud computing technologies make collecting, processing, and analysing the so-called big data possible. The monitoring and visualization of information aid in personalizing applications that benefit both homeowners and researchers in analysing consumer profiles. This paper presents a smart meter for household (SMH) to obtain load profiles and a new platform that allows the innovative analysis of captured Internet of Things data from smart homes, photovoltaics, and electrical vehicles. We propose the use of cloud systems to enable data-based services and address the challenges of complexities and resource demands for online and offline data processing, storage, and classification analysis. The requirements and system design components are discussed.

**Keywords:** internet of things; data acquisition; cloud computing; big data analytics; load profile; smart meter
