From Data Harvesting to Querying for Making Urban Territories Smart

TL;DR

This chapter critically reviews data-centric urban computing solutions, from data harvesting to decision support, highlighting strategies and guidelines for addressing urban challenges using data science techniques.

Contribution

It provides a comprehensive analysis of current urban data solutions, proposing a methodological framework for understanding and applying these strategies.

Findings

Data harvesting techniques are foundational for urban computing.

Decision support systems enhance urban problem-solving.

Strategic guidelines can improve implementation of data-centric solutions.

Abstract

This chapter provides a summarized, critical and analytical point of view of the data-centric solutions that are currently applied for addressing urban problems in cities. These solutions lead to the use of urban computing techniques to address their daily life issues. Data-centric solutions have become popular due to the emergence of data science. The chapter describes and discusses the type of urban challenges and how data science in urban computing can face them. Current solutions address a spectrum that goes from data harvesting techniques to decision making support. Finally, the chapter also puts in perspective families of strategies developed in the state of the art for addressing urban problems and exhibits guidelines that can lead to a methodological understanding of these strategies.