Housing costs have a significant impact on individuals, families, businesses, and governments. Recently, online companies such as Zillow have developed proprietary systems that provide automated estimates of housing prices without the immediate need of professional appraisers. Yet, our understanding of what drives the value of houses is very limited. In this paper, we use multiple sources of data to entangle the economic contribution of the neighborhood's characteristics such as walkability and security perception. We also develop and release a framework able to now-cast housing prices from Open data, without the need for historical transactions. Experiments involving 70,000 houses in 8 Italian cities highlight that the neighborhood's vitality and walkability seem to drive more than 20% of the housing value. Moreover, the use of this information improves the nowcast by 60%. Hence, the use of property's surroundings' characteristics can be an invaluable resource to appraise the economic and social value of houses after neighborhood changes and, potentially, anticipate gentrification.

[DSAA 2018] [arXiv]

Policy makers, urban planners, architects, sociologists, and economists are interested in creating urban areas that are both lively and safe. But are the safety and liveliness of neighborhoods independent characteristics? In this paper we explore the connection between the levels of activity and the perception of safety of neighborhoods in two major Italian cities by combining mobile phone data (as a proxy for activity or liveliness) with scores of perceived safety estimated using a Convolutional Neural Network trained on a dataset of Google Street View images scored using a cgrid-xdsourced visual perception survey.

[ACM MM16] [arXiv] [Fast Co.design]

The Death and Life of Great American Cities was written in 1961 and is now one of the most influential book in city planning. In it, Jane Jacobs proposed four conditions that promote life in a city. However, these conditions have not been empirically tested until recently. We operationalized these conditions extracting information from Open Data, Foursquare and mobile phone data and testing them in six Italian cities.

[WWW-2016] [arXiv] [MIT Technology Review] [Fast Company]

The Mobile Territorial Lab: A multilayered and dynamic view on parents' daily lives

Description of the Mobile Territorial Lab (MTL) project, a longitudinal living lab which has been sensing by means of technology (mobile phones) the lives of more than 100 parents in different areas of the Trentino region in Northern Italy. We present the preliminary results after two years of experimentation of, to the best of our knowledge, the most complete picture of parents’ daily lives.

[EPJ Data Science]

A multi-source dataset of urban life in the city of Milan and the Province of Trentino

Description of the richest open multi-source dataset ever released on two geographical areas. The dataset is composed of telecommunications, weather, news, social networks and electricity data from the city of Milan and the Province of Trentino.

[Nature Scientific Data]

Investigating the relationships between spatial structures and urban characteristics (NETMOB2015 at MIT)

Analysis of the communication networks of 12 Italian cities with more than 150'000 inhabitants in order to investigate the impact of cities' spatial structures and dynamics on different socioeconomic outcomes such as economic growth, innovation, contagious disease rates and crime.

Short-term anomaly detection in gas consumption through ARIMA and Artificial Neural Network forecast

[EESMS 2015] [source code]