Detección de Automóviles en Escenarios Urbanos Escaneados por un Lidar

Load profiles of energy consumption from smart meters are becoming more and more available, and the amount of data to analyse is huge. In order to automate this analysis, the application of state-of-the-art data mining techniques for time series analysis is reviewed. In particular, the use of dynamic clustering techniques to obtain and visualise temporal patterns characterising the users of electrical energy is deeply studied. The performed review can be used as a guide for those interested in the automatic analysis and groups of behaviour detection within load profile databases. Additionally, a selection of dynamic clustering algorithms have been implemented and the performances compared using an available electric energy consumption load profile database. The results allow experts to easily evaluate how users consume energy, to assess trends and to predict future scenarios.

show abstract

Detección de Automóviles en Escenarios Urbanos Escaneados por un Lidar

Cited by 2 publications

References 14 publications

A MATLAB-Based Tool for 3D Reconstruction Technologies for Indoor and Outdoor Environments

A MATLAB-Based Tool for 3D Reconstruction Technologies for Indoor and Outdoor Environments

Automated Detection of Electric Energy Consumption Load Profile Patterns

Contact Info

Product

Resources

About