Integrating environmental data, citizen science and personalized predictive modeling to support public health in cities: The PULSE WebGIS

Parimbelli, Enea and Pala, Daniele and Bellazzi, Riccardo and Vera Muñoz, Cecilia and Casella, Vittorio (2018). Integrating environmental data, citizen science and personalized predictive modeling to support public health in cities: The PULSE WebGIS. In: "Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)", 07/02/2018 - 07/02/2018, New Orleans, Louisiana, USA. pp. 495-498.

Description

Title: Integrating environmental data, citizen science and personalized predictive modeling to support public health in cities: The PULSE WebGIS
Author/s:
  • Parimbelli, Enea
  • Pala, Daniele
  • Bellazzi, Riccardo
  • Vera Muñoz, Cecilia
  • Casella, Vittorio
Item Type: Presentation at Congress or Conference (Article)
Event Title: Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)
Event Dates: 07/02/2018 - 07/02/2018
Event Location: New Orleans, Louisiana, USA
Title of Book: Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)
Date: 2018
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Tecnología Fotónica y Bioingeniería
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The percentage of the world's population living in urban areas is projected to increase significantly in the next decades. This makes the urban environment the perfect bench for research aiming to manage and respond to dramatic demographic and epidemiological transitions. In this context the PULSE project has partnered with five global cities to transform public health from a reactive to a predictive system focused on both risk and resilience. PULSE aims at producing an integrated data ecosystem based on continuous large-scale collection of information available within the smart city environment. The integration of environmental data, citizen science and location-specific predictive modeling of disease onset allows for richer analytics that promote informed, datadriven health policy decisions. In this paper we describe the PULSE ecosystem, with a special focus on its WebGIS component and its prototype version based on New York city data.

Funding Projects

TypeCodeAcronymLeaderTitle
Horizon 2020727816PULSEUNIVERSIDAD POLITECNICA DE MADRIDParticipatory Urban Living for Sustainable Environments

More information

Item ID: 55195
DC Identifier: http://oa.upm.es/55195/
OAI Identifier: oai:oa.upm.es:55195
Deposited by: Memoria Investigacion
Deposited on: 01 Jul 2019 16:02
Last Modified: 01 Jul 2019 16:02
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