THANOS: Towards a healthy smart metropolis. Data-driven multidisciplinary strategies for pursuing sustainable mobility

"This project encompasses three main objectives:
Objective 1: Using ICTs and a systematic data collection process, we can obtain a massive amount of data in real-time to complement existing data repositories and feed health-related applications. Hence, we aim to design a scalable data storage and processing pipeline deployed on top of a cloud computing infrastructure able to collect and store sensors’ multimodal data.
Objective 2: Integrating heterogeneous and decentralized data from IoT-based devices and sensors–many of them located in public spaces and facilities–, and by employing predictive analytics algorithms (machine learning and data mining) we will build effective systems for automatic inference and recommendation of disease diagnosis and treatment. In this objective, we will also present also the use of digital transformation in processes of urban design through Virtual Reality in which specialized and non-specialized public can analyze, represent and transmit ideas, problems and solutions for the design of the urban uses and spaces.
Objective 3: Upon the insights extracted from the collected data, we will study the particularities of the historic city, compared with the contrasts generated in modern urbanism and with the socio-urban dynamics that are reflected in the recent developments of popular urbanism in the peripheral areas of cities. The decisive influence of new technologies (and its education) is important for the generation of a new reality from the economic, social and urban point of view. In this regard we will create a complement for decision support systems that uses a prediction model to understand and better explain both, in educational and professional framework how every variable that architects and urban policies use to design our cities will affect citizens’ health and, in consequence, how architects, local entities, and the same citizens could improve their health by optimizing the urban design.
"

"This project encompasses three main objectives:
Objective 1: Using ICTs and a systematic data collection process, we can obtain a massive amount of data in real-time to complement existing data repositories and feed health-related applications. Hence, we aim to design a scalable data storage and processing pipeline deployed on top of a cloud computing infrastructure able to collect and store sensors’ multimodal data.
Objective 2: Integrating heterogeneous and decentralized data from IoT-based devices and sensors–many of them located in public spaces and facilities–, and by employing predictive analytics algorithms (machine learning and data mining) we will build effective systems for automatic inference and recommendation of disease diagnosis and treatment. In this objective, we will also present also the use of digital transformation in processes of urban design through Virtual Reality in which specialized and non-specialized public can analyze, represent and transmit ideas, problems and solutions for the design of the urban uses and spaces.
Objective 3: Upon the insights extracted from the collected data, we will study the particularities of the historic city, compared with the contrasts generated in modern urbanism and with the socio-urban dynamics that are reflected in the recent developments of popular urbanism in the peripheral areas of cities. The decisive influence of new technologies (and its education) is important for the generation of a new reality from the economic, social and urban point of view. In this regard we will create a complement for decision support systems that uses a prediction model to understand and better explain both, in educational and professional framework how every variable that architects and urban policies use to design our cities will affect citizens’ health and, in consequence, how architects, local entities, and the same citizens could improve their health by optimizing the urban design.
"