H-index - A Novel Multi-Criteria Happiness Index for Cities

 

Academic Track

The idea

The project aims to provide a quality of life index that we call the Happiness Index (or H-index). Making use of the TIM Big Data Challenge datasets, this index is computed from three spatio-temporal indicators: living environment, mobility and social interaction. These sub-indexes are based on simple assumptions on major factors impacting quality of life. Our methodology allows the assessment of the well-being of citizens and the comparison of results between geographical areas (e.g. cities) using understandable and relevant criteria.

Many studies employ surveys and scoring systems to define the quality of city life. These methods, however, often produce contradictory results and are expensive to put into practice. Moreover, the available data is not always up-to-date, and therefore not truly representative of the particular locations. In contrast, the TIM Big Data Challenge 2015 datasets provide accurate, up-to-date metrics of the population. The H-index delivers concrete indications of how administrations and planners can best enhance the happiness of citizens. It helps identifying which areas would likely be most impactful and thus important to invest in (e.g. implementing congestion reduction, renovation and city planning). Furthermore, the H-index can be scaled down to the city district level, to allow more detailed evaluation of the different indicators. We are convinced that by improving the quality of life of citizens, it is possible to improve the productivity of a city as well as its competitiveness.

Future developments include the improvement of the significance of our index and its indicators by including additional data sources and socio-economical indicators. Moreover, there will be a deeper analysis of possible correlations and an enhancement of our assumptions and model. Another of our goals is the development of a procedure for adequately weighting the indicators, by finding correlations with other studies.

 
 

The Team

Uni.Lu

The team members are researchers at the interdisciplinary research center of the University of Luxembourg (SnT) and part of the VehicularLab research group.

Thierry Derrmann
Thierry Derrmann is PhD student at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) of the University of Luxembourg (UL). He received his Computer Sciences diploma (Dipl.-Inf.) at the Karlsruhe Institute of Technology (KIT, Germany) in 2011. During his diploma thesis he worked on the design of filtering algorithms using GPUs for applications in the field of mass spectrometry. His current research interests are related to data analysis, traffic optimization and mobility applications and stochastic modeling. His PhD project on multimodal mobility models is funded by the National Research Fund of Luxembourg (FNR).

Dr. Sébastien Faye
Sébastien Faye obtained his PhD degree from Télécom ParisTech (Paris, France) in 2014. After completing his Master, Sébastien carried out a number of studies on wireless sensor networks and the security mechanisms they offer. During his Ph.D, he studied ways in which such distributed systems can manage intelligent transportation systems, investigating their deployment and performance in the area of traffic light management. Since 2014, he is Research Associate at the University of Luxembourg (SnT). His research interests are wireless sensor networks, mobile computing, hierarchy and partitioning, intelligent transportation systems.

Dr. German Castignani
German Castignani is research associate at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) of the University of Luxembourg (UL). He received his Computer Sciences Engineer degree at the University of Buenos Aires (FIUBA, Argentina) and a PhD in Computer Sciences at Institut Mines-Telecom, Telecom Bretagne (Rennes, France). He has more than 30 scientific publications in conference proceedings and international peer-reviewed journals. His research interests include Vehicular and Wireless Networks, Mobility Management, Intelligent Transportation Systems (ITS) and Advanced Driving Assistance Systems. Currently, Dr. Castignani works on several research projects at the VehicularLab, including handover management in IEEE 802.11 V2I communications, mobile sensing, driver profiling and crowdsourcing for driving assistance systems.

Dr. Raphael Frank
Raphael Frank is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg and head of the VehicularLab. Dr. Frank received his Ph.D. in Computer Science from the University of Luxembourg in 2010. During his Ph.D. studies, he was a visiting scholar at the University of California in Los Angeles (UCLA) where he conducted research on data routing protocols for vehicular networks. In 2006, he received his Master Degree in Cryptography and Network Security from the University Joseph Fourier in Grenoble, France. He is currently involved in several European and national research projects. His research interests include wireless networks and mobile computing. He is member of the Car-2-Car Communication Consortium, German Computer Science Society (GI), IEEE, ACM and the IPv6 Forum Luxembourg. Dr. Frank is on the editorial board of the Springer Wireless Networks (WINET) journal. He regularly serves in technical program committees of leading conferences and journals.

 

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