Smart territories

The concept of smart cities is relatively new in research. Thanks to the colossal advances in Artificial Intelligence that took place over the last decade we are able to do all that that we once thought impossible; we build cities driven by information and technologies. In this keynote, we are going to look at the success stories of smart city-related projects and analyse the factors that led them to success. The development of interactive, reliable and secure systems, both connectionist and symbolic, is often a time-consuming process in which numerous experts are involved. However, intuitive and automated tools like “Deep Intelligence” developed by DCSc and BISITE, facilitate this process. Furthermore, in this talk we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems, as well as the use of edge platforms or fog computing

Distributed Prediction of Carbon Dioxide Exchange Using CBR-BDI Agents.

This paper presents a model constructed for the evaluation of the interaction of the atmosphere and the ocean. The work here presented focuses in the development of an agent based architecture that has been constructed for the evaluation of the interaction, between the atmosphere and the ocean waters, of several parameters. Such evaluation needs to be made continuously in a dynamic environment and therefore requires the use of autonomous models that evolve with the time. The proposed architecture incorporates CBR-agents whose aim is to monitor the evolution of the interaction of parameters and facilitate the creation of an explanation model. The system has been tested and this paper presents the results obtained

Deliberative Agents for Distributed Monitoring and Evaluation of the Air-Sea Interaction.

This paper presents a model constructed for the evaluation of the interaction of the atmosphere and the ocean. The work here presented focuses in the development of an agent based architecture that has been constructed for the evaluation of the interaction, between the atmosphere and the ocean waters, of several parameters. Such evaluation needs to be made continuously in a dynamic environment and therefore requires the use of autonomous models that evolve with the time. The proposed architecture incorporates CBR-agents whose aim is to monitor the evolution of the interaction of parameters and facilitate the creation of an explanation model. The system has been tested and this paper presents the results obtained

Smart Buildings

This talk presents an efficient cyberphysical platform for the smart management of smart buildings http://www.deepint.net. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart building is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study at Salamanca - Ecocasa. This platform could enable smart building to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques