Big Data for Sensing
Robert C. Qiu, Paul Antonik · 2017
This chapter considers a sensing system as a big data system and models the massive amount of data with the aid of large random matrices. An emerging field is the use of wireless sensor networks (WSNs) as a support for smart grids. In such a case, a WSN is useful to: monitor and predict energy production from renewable sources of energy such as wind or solar energy, monitor energy consumption, and detect anomalies in the network. The proper way to describe the interactions among the network nodes is to introduce the graph model of the network. Euclidean random matrices play an important role in description of many physical models including the electronic levels in a morphous systems, very diluted impurities, and the spectrum of vibrations in glasses. The chapter talks about the connection between, the Euclidean random matrix and the massive MIMO (or WSN).