Smart Cities

La Salle R&D offers multidisciplinary testbed for Smart Services by using the involvement of Campus La Salle international:

  • Barcelona and Madrid (Spain)
  • Almere (Holland)
  • UOLS, La Salle Open University (Global scope)

Leading from the Business, Architecture and Engineering Schools and targeting:

  • Education
  • Future Network Architectures
  • Utilities and Smart Grids

La Salle R&D is developing and testing a complete city centric ambient data network with the objective of integrating intimately the data on the state of the city, even locally, to provide the necessary feedback for the control mechanisms to react properly with the objective of optimizing energy usage,  sustainability and minimizing carbon emissions. Sustainable city networks should be a highly distributed concept involving sensors, actuators, computers and communications in a very dynamic environment. Smart Cities must include the following concepts:

Sensing: By means of energy harvesting powered ubiquitous sensors with no maintenance required, plant, soil and other environmental parameters are registered. Integrated view as an IoT (Internet of Things) would provide a new height of knowledge and control. In this scenario, standards of communication protocols, information representation models, modules interfaces and processes are crucial.

Data collection: Using heterogeneous sensor network technologies, the data is transported from the sensor to the data concentrator, giving access to this data to be sent to the central system. It is needed a global solution with regard to cyber-security, trust management, QoS-aware communications and mobility among others. Growing needs of storage for the media content has to be managed (Big Data).

Analysis: The analysis is based on a distributed data storage repository inspired by the current cloud computing technologies. By combining the data gathered from the different house based fields and other coming from third services (Open Data), like weather information, citized-centric information, crowd sourcing, traffic and people flows, agricultural demand forcasting, big producers capacity, etc, diferent metrics and key performance indexes can be extracted.

Decision support: Those metrics and key performance indexes are aggregated and presented in a way the information can be easily and usefully consumed by government in order to make correct decisions when driving its diferent policies.

Smart CitiesAgustin Zaballoszaballos@salle.url.edu