The scientific program of CityLab@Inria has the aim of putting the citizens at the center of the development of smart cities, so that it hopefully fosters both social and environmental sustainability. This is made possible in particular by the mass adoption of e-communication where (smart) phones and social networking are the two key pillars that allow citizens to be aware about city development as much as to contribute and even influence the evolution of the city. The open data trend is also a significant source of awareness for the citizens.
The Lab specifically investigates the following research questions:
- How to effectively sustain privacy-preserving urban-scale sensing and actuation that need to combine both physical and social sensing and actuation while accounting for the requirements associated with the target network that include: scalability, energy-efficiency, and security? The sensing of the city pulse also challenges the supporting data management, which must scale-up as well as integrate highly heterogeneous data of various qualities. The literature is rich with papers addressing these concerns individually. However, these are seldom tackled together, especially while simultaneously considering the urban scale. Our approach to overcome these challenges lies in the study of:
- How to aggregate urban data so as to understand but also anticipate and even influence the evolution of the city? Data analytics is at the core of smart cities so that the “big data” that is made available to us by way of physical as much as social sensing, but also based on the open data trend can indeed become useful knowledge about the cities. Data analytics for smart cities is a very active area of research. However, numerous open problems remain among which large-scale data analysis and overcoming the uncertainty associated with urban-scale, crowd-sourced data collection. Our contribution in this area leverages advanced research results on data assimilation and machine learning:
While city-scale sensing and data analytics are two complementary aspects of smart city systems, they are also inter-related as one should inform the design of the other, and vice versa. It is then essential to design crosscutting architectures for smart city systems based on the comprehensive integration of the custom data sensing and analytics that we will investigate.
The scientific focus of CityLab@Inria is broad, leveraging relevant effort within Inria project-teams that is further revisited as well as integrated to meet the challenges of smart cities. In addition, CityLab@Inria research builds upon international research collaborations, and especially collaboration in the context of the Inria@SiliconValley program.
