Major advances in ICTs allow to consider citizens as sensors in motion. Carrying their mobile devices, moving in their connected vehicles and actively participating in social networks, citizens provide a wealth of information that, after processing, can support numerous applications for the benefit of the community. In the context of smart communities, INRISCO intends (i) the early detection of abnormal situations in cities (incidents), (ii) the analysis of whether, according to their impact, those incidents are really adverse for the community; and (iii) the automatic actuation by dissemination of appropriate information to citizens and authorities. Thus, INRISCO will identify and report on incidents in traffic (jam, accident) or public infrastructure (works, street cut); the occurrence of specific events that affect other citizens’ life (demonstrations, concerts); or environmental problems (pollution, bad weather). It is of particular interest to this proposal the identification of incidents with a social and economic impact which affects the quality of life of citizens.
INRISCO does not intend to replace the current emergency management services (e.g. 112), but rather to improve the warning systems and complement them to manage adverse situations which have an impact in the citizens. In this regard, INRISCO aims to effectively address two key issues: early detection and dissemination of information. In the current technological context, it is feasible to obtain objective and subjective information from the new “citizen sensor”: objective, thanks to physical sensors in their devices and in the smart city, and subjective, thanks to opinions/comments posted on online social networks. The analysis of this massive amount of data (so-called Big Data) from structured and unstructured sources enables early detection of abnormal situations as well as the estimation of their impact in the community. Going further, actuation is also possible by disseminating alert messages and suggested actions: globally, through online social networks, and locally, through ad-hoc or opportunistic networks dynamically built up in the community.
To ensure the citizens’ participation, reliability, security, flexibility and privacy must be covered as requirements about which citizens are especially concerned. Firstly, it is crucial to ensure the accuracy of the information collected. Secondly, it is essential to ensure an adequate level of privacy to citizens, so that sensitive information (such as location, preferences, or other personal information) does not flow through social networks or is collected by third parties without their explicit consent. Lastly, the proposal also cannot ignore the volume, velocity and variety of data provided by the citizens, as well as the critical nature of the detected situations and services involved.
For the integration of the main results of the project, INRISCO proposes a demonstrator for the early detection of adverse events and the efficient and effective dissemination of warnings. That demonstrator will be deployed over a dataset which integrate real sensor data from a city, and a real data set collected from a public online social network.
Team
INRISCO. QoS And Privacy – UPC
Mónica Aguilar Igartua, PhD (Coordinator, UPC’s Principal Investigator 1)
Jordi Forné, PhD (UPC’s Principal Investigator 2)
Luis de la Cruz Llopis, PhD
Francisco Rico Novella, PhD
Isabelle Guérin-Lassous, PhD
Azzedine Boukerche, PhD (Advisory Board)
Silvia Puglisi
Luis Urquiza Aguiar
Ahmad Mohammad Mezher
Christian René Iza Paredes
INRISCO. Security And Mobility – UC3M
Florina Alemenárez Mendoza, PhD (UC3M’s Principal Investigator)
Celeste Campo Vázquez, PhD
Alberto Cortes Martín, PhD
Daniel Díaz Sánchez, PhD
Carlos García Rubio, PhD
Andrés Marín López, PhD
Elena Yndurain, PhD
Patricia Arias Cabarcos, PhD
Estrella M. García Lozano
Alicia Rodríguez Carrión
INRISCO. Crowd Sensing Based On Social Mining – UVIGO ICLAB
Rebeca P. Díaz Redondo, PhD (UVIGO’s Principal Investigator)
Ana Fernández Vilas, PhD
Antonio Capone, PhD
Mohamed Ben Khalifa
Kais Dai
Celia González Nespereira
Fátima Castro Jul
Miran Boric
Sheila Lucero Sánchez
INRISCO. Security, Privacy And Big Data – GRADIANT
Manuela I. Martín Vicente, PhD (GRADIANT’s Principal Investigator)
Rafael P. Martínez Álvarez, PhD
Daniel A. Rodríguez Silva, PhD
Héctor Cerezo Costas
Gregorio Nuevo Castro
Víctor Alonso Macías
Vanesa Fernández Díaz
Advisory Board
Prof. Azzedine Boukerche, University of Ottawa, Canada
Prof. Claudia Díaz, KU Leuven, Nederland.
Prof. Elena Ferrari, University of Insubria, Italy
PhD. Yiannis Kompatsiaris, Centre of Research & Technology, Greece