Participatory urban living for sustainable environments
Concept
A paradigm shift toward a data-driven socio-economic model is occurring as a result of the increased volume, velocity and variety of data. Powerful tools have been developed to collect, store, analyse, process and visualize large amounts of data. Open data initiatives have been launched to provide broad access to data from the public sector, business and science. Europe is still in the early stages of adopting Big Data technologies and services. Successful adoption of Big Data will require changes in business orientation and strategy, and the functioning of public sector agencies.
BigData
PULSE (Participatory Urban Living for Sustainable Environments) will leverage diverse data sources and big data analytics to transform public health from a reactive to a predictive system, and from a system focused on surveillance to an inclusive and collaborative system supporting health equity.
Five Global Cities
Working within five global cities, PULSE will harvest open city data, and data from health systems, urban and remote sensors, personal devices and social media to enable evidence-driven and timely management of public health events and processes.
Clinical Focus
The clinical focus of the project will be respiratory diseases (asthma) and metabolic diseases (Type 2 Diabetes) in adult populations. The project will develop risk stratification models based on modifiable and non-modifiable risk factors in each urban location, taking account of biological, behavioural, social and environmental risk factors.
Aims
PULSE will engage in a collaborative dialogue with a range of stakeholders across five global cities to transform public health from a reactive to a predictive system focused on both risk and resilience. In order to achieve this, the operation objectives are:
- To develop multi-scale models designed to integrate diverse data, identify and share new knowledge, uncover mechanisms, and make predictions about intervention effects.
- To develop of the PULSE integrated data ecosystem based on mobile devices (smart phones), sensor systems (remote sensing, including satellites and Unmanned Aerial Vehicles [UAVs]; fixed and mobile sensors) to enable large scale collection of citizen data within the smart city environment.
- To develop new approaches to data mining for public health outcomes.
- To develop advanced models for the detection of risks associated with the onset of Asthma and T2D
- To develop a population-based algorithm to detect well-being across our test bed cities
- To develop a generalizable framework for delivering digital interventions in the context of urban public health, addressing existing and emerging risks and threats, and building resilience at the individual and community level
- To design and build of a large-scale data management system enabling real time analytics of flows of personal data in a trusted cloud.
- To develop a policy-making across the domains of health, environment, transport, planning in the PULSE test bed cities,
- To develop a proof-of-concept of the PULSE Risk and Resilience models within five global cities (300 citizens-users of PULSE apps/game in each test bed; 1500 in total)
- To define a suite of sustainable and generalizable multi-scale models for detecting public health risks related to Asthma and T2D, and intervening to mitigate these risks, minimize health inequities, and improve population health
Funding
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No GA727816.