Lecture Title: Managing Future Risk and Interdependency for Smart Sustainable Cities
Presented By: Martino Tran, University of British Columbia
Abstract: Cities contain over half the world’s population, consume two-thirds of global energy, and are highly vulnerable to climate change. Advances in information technology enabling more intelligent and responsive urban infrastructure has the potential to improve city operations and manage demand.
Historically, planning and investment for urban infrastructure has been done sector-by-sector, but infrastructure is becoming more interdependent due to rising cross-sector demands, climate change policy and increasing use of information and communication technologies (ICT). Cities will increasingly depend on ICT for capacity provision (pervasive sensor networks enabling autonomous control) and delivery of services (on-demand transport).
However, the long-term sustainability implications for smart infrastructure provision and investment are not well understood. Fundamental questions remain including: How can we avoid lock-in to environmentally damaging infrastructure? To what extent can we predict future impacts, and manage risk across urban sectors? This talk will explore long-term critical interdependency between sectors (buildings, power, transport, ICT) and discuss the use of ubiquitous urban data, and predictive modelling and simulation to inform sustainable urban policy and planning.
Biography: Martino is Director of the Urban Predictive Analytics Lab, Co-Director of the Master of Engineering Leadership in Urban Systems, and Assistant Professor in the School of Community and Regional Planning at UBC. Martino's research focuses on predictive modelling and simulation of urban infrastructure and technology to inform policy and investment strategies with positive societal and sustainability outcomes. Martino has led both technical and policy research for government, academia and industry on the large-scale deployment of smart energy and transport technologies. He holds a PhD in Environmental Science specializing in computational modelling and simulation from the University of Oxford. His thesis applied systems engineering and complex network theory to model early adoption of electric vehicles for climate change mitigation.
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