Abstract
This chapter illustrates a geostatistic model (Chapter 4) application to estimate quasi real-time energy consumption in each building using Google's Popular Times data. After the introduction in Section 11.1 where our research motivations are explained, Section 11.2 describes the empirical methods, and we adopt compositional kriging approach for this analysis. Section 11.3 shows the estimation results of estimating building-level energy consumption. Effective visualization is attempted with the results. Section 11.4 concludes this chapter with a discussion.
| Original language | English |
|---|---|
| Title of host publication | Spatial Analysis Using Big Data |
| Subtitle of host publication | Methods and Urban Applications |
| Publisher | Elsevier |
| Pages | 271-280 |
| Number of pages | 10 |
| ISBN (Electronic) | 9780128131329 |
| ISBN (Print) | 9780128131275 |
| DOIs | |
| Publication status | Published - 2019 Nov 2 |
| Externally published | Yes |
Keywords
- Compositional kriging
- Energy demand estimation
- Popular Times
- Real time
- Smart community
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Business, Management and Accounting(all)
