Smart Cities: How Data Mining and Optimization Can Shape Future Cities
Abstract
By 2050, an estimated 70% of the worlds population will live in cities up from 13% in 1900. Already, cities consume an estimated 75% of the worlds energy, emit more than 80% of greenhouse gases, and lose as much as 20% of their water supply due to infrastructure leaks. As their urban populations continue to grow and these metrics increase, civic leaders face an unprecedented series of challenges to scale and optimize their infrastructures.
Cite
Text
Verscheure. "Smart Cities: How Data Mining and Optimization Can Shape Future Cities." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2011. doi:10.1007/978-3-642-23780-5_10Markdown
[Verscheure. "Smart Cities: How Data Mining and Optimization Can Shape Future Cities." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2011.](https://mlanthology.org/ecmlpkdd/2011/verscheure2011ecmlpkdd-smart/) doi:10.1007/978-3-642-23780-5_10BibTeX
@inproceedings{verscheure2011ecmlpkdd-smart,
title = {{Smart Cities: How Data Mining and Optimization Can Shape Future Cities}},
author = {Verscheure, Olivier},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2011},
pages = {11},
doi = {10.1007/978-3-642-23780-5_10},
url = {https://mlanthology.org/ecmlpkdd/2011/verscheure2011ecmlpkdd-smart/}
}