Smart electricity meters allow capturing consumption load profiles of residential buildings. Besides several other applications, the retrieved data renders it possible to reveal household characteristics including the number of persons per apartment, age of the dwelling, etc., which helps to develop targeted energy conservation services. The goal of this chapter is to develop further related methods of smart meter data analytics that infer such household characteristics using weekly load curves. The contribution of this chapter to the state of the art is threefold. The authors first quadruplicate the number of defined features that describe electricity load curves to preserve relevant structures for classification. Then, they suggest feature filtering techniques to reduce the dimension of the input to a set of a few significant ones. Finally, the authors redefine class labels for some properties. As a result, the classification accuracy is elevated up to 82%, while the runtime complexity is significantly reduced.
As part of a long-term project to investigate the cultural history of the Nasca region in southern Peru, the famous
Nasca lines, or geoglyphs, have been documented since 1997 in a joint effort by archaeologists and geomatic engineers. The
project aims on the one hand at a new interpretation of the geoglyphs based on solid field data. On the other hand, it is thought
of as a contribution to the preservation of the geoglyphs. Prior to the start of the project, the geoglyphs had never been
adequately recorded. In a new approach that combined aerial photogrammetry with archaeological fieldwork, we thoroughly
documented more than 1 500 geoglyphs in the vicinity of Palpa. While different aspects of this work have been described in
previous reports, this paper offers an overview of the technical procedures from data acquisition to processing, modeling, and