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INRISCO
INcident MonitoRing In Smart COmmunities - Monitorizacion de incidentes en comunidades inteligentes: seguridad y movilidad
Spanish Ministerio de Economía y Competitividad
Proyectos de I+D+I del programa estatal de investigacion, desarrollo e innovacion orientada a los retos de la sociedad
(Ref. TEC2014-54335-C4-2-R)
01/ 2015 -- 06/ 2019
Abstract
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."
Publications

AGUILAR-IGARTUA, MÓNICA; ALMENARES-MENDOZA, FLORINA; DÍAZ-REDONDO, REBECA; MARTÍN-VICENTE, MANUELA; FORNÉ, JORDI; CAMPO, CELESTE; FERNÁNDEZ-VILAS, ANA; CRUZ-LLOPIS, LUIS; GARCÍA-RUBIO, CARLOS; MARÍN-LÓPEZ, ANDRÉS; MOHAMAD-MEZHER, AHMAD; DÍAZ-SÁNCHEZ, DANIEL; CEREZO-COSTAS, HÉCTOR; REBOLLO-MONEDERO, DAVID; ARIAS-CABARCOS, PATRICIA; RICO-NOVELLA, FRANCISCO JOSÉ

INRISCO: INcident monitoRing in Smart COmmunities Journal Article

In: IEEE Access, vol. 8, pp. 72435 - 72460, 2020, ISSN: 2169-3536.

Abstract | Links | BibTeX

Campo-Vázquez, Celeste; García-Rubio, Carlos; Martí, Mónica

Performance Evaluation of CoAP and MQTT_SN in an IoT Environment Conference

Proceedings of 13th International Conference on Ubiquitous Computing and Ambient ‪Intelligence UCAmI 2019, MDPI AG , 2019.

Abstract | Links | BibTeX

Campo-Vázquez, Celeste; García-Rubio, Carlos; Rodriguez-Carrion, Alicia

Detecting and reducing biases in cellular-based mobility data sets Journal Article

In: Entropy, vol. 20, iss. 10, 2018, ISSN: 1099-4300.

Abstract | Links | BibTeX

Rubio-Drosdov, E; Díaz-Sánchez, D; Almenárez, F; Arias-Cabarcos, P; Marín, A

Seamless human-device interaction in the internet of things Journal Article

In: IEEE Transactions on Consumer Electronics, vol. 63, iss. 4, pp. 490-498, 2017, ISSN: 1558-4127.

Abstract | Links | BibTeX

Campo-Vázquez, Celeste; García-Rubio, Carlos; García-Lozano, Estrella; Rodriguez-Carrion, Alicia

A Bandwidth-Efficient Dissemination Scheme of Non-Safety Information in Urban VANETs Journal Article

In: Sensors , vol. 16, iss. 7, 2016, ISSN: 1424-8220.

Abstract | Links | BibTeX

Khaled, Omar; Marín, Andrés; Almenares, Florina; Arias, Patricia; Díaz, Daniel

Analysis of Secure TCP/IP Profile in 61850 Based Substation Automation System for Smart Grids Journal Article

In: International Journal of Distributed Sensor Networks, vol. 12, iss. 4, 2016, ISSN: 1550-1477.

Abstract | Links | BibTeX

Almenarez, Florina; Hinarejos, M. Francisca; Marín, Andrés; Ferrer-Gomila, Josep Lluís; Sánchez, Daniel Díaz

PECEVA: An adaptable and energy-saving credential validation solution for pervasive networks Journal Article

In: INFORMATION SCIENCES, vol. 354, pp. 41-59, 2016, ISSN: 0020-0255.

Abstract | Links | BibTeX

Campo-Vázquez, Celeste; Vara, Isabel

Cross-Layer Service Discovery Mechanism for OLSRv2 Mobile Ad Hoc Networks Journal Article

In: Sensors , vol. 15, iss. 7, pp. 17621-17648, 2015, ISSN: 1424-8220.

Abstract | Links | BibTeX

More Information

INRISCO – Monitorizacion de incidentes en comunidades inteligentes: seguridad y movilidad

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