This proposal is organized around two big ideas: 1) explore the potential expressive analysis of the continuous and large amounts of information sensed in urban environments can boost the understanding of human mobility patterns in urban cities; 2) enhance access data and knowledge to citizens, stakeholders and researchers to improve their ability to utilize live information that will help achieve social, economic and environmental sustainability in cities. Two projects will be conducted: we will explore the validity and analytical strength of using geotagged social media data for understanding urban activity and mobility pattern. In the second project, we will leverage state-of-the-art analytics to observe, alert, predict and share live congestion information associated with traffic incidents in urban cities. The proposal seeks to improve the education of next generation urban experts across disciplines within and beyond the research network, and engage stakeholders to accelerate the transfer of promising knowledge and innovations. The study of using big data to characterize mobility patterns of cities is by itself a discovery process regarding the validity, strengths and weaknesses, and the kind of questions suitable with the data and methodology. By joining the different research participants’ expertise and leveraging big data and state-of-the-art streaming analytics, this project will significantly advance state-of-the-art urban mobility and congestion applications.
Professor at Energy and Environment, Physical Resource Theory
Funding years 2017–2019
Chalmers Driving Force