Subventions et des contributions :

Titre :
Green software-defined platform for smart city big data applications
Numéro de l’entente :
STPGP
Valeur d'entente :
900 000,00 $
Date d'entente :
18 oct. 2017 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Ontario, Autre, CA
Numéro de référence :
GC-2017-Q3-00813
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2020-2021).

Nom légal du bénéficiaire :
Leon-Garcia, Alberto (University of Toronto)
Programme :
Projets stratégiques - groupe
But du programme :

By 2050, over 70% of the world's population will live in cities that occupy only 2% of the world's land mass and consume 75% of its resources, leading to challenges on how to maintain economic advancement, environmental sustainability, and social resiliency. Smart city technologies (cloud computing, software-defined networking, Internet of Things) can help address these challenges by enabling open software application platforms that allow cities to tackle challenges such as traffic congestion, air and noise pollution, safety and crime, emergency response, climate change, economic growth, and delivery of city services. Our goal is to design and deploy a smart city application platform and to demonstrate smart city applications. In a typical application, sensors gather the data on human activity, urban systems and the environment, cloud computing formulates a plan for coordinated beneficial behaviour, and networking carries control messages to actuators. For example, a smart transportation application may coordinate all modes of travel in a region so that travel times are optimized and energy consumption, pollution and carbon footprint are minimized. Other applications will address autonomous vehicles, energy generation and consumption to minimize carbon footprint, emergency response, and transparent community dashboards for city outcomes and performance. In this research we will integrate the management of geographically-distributed sensing, networking, computing, and actuation resources to create a platform that supports smart city applications for private and public service providers as well as individual citizens. This entails developing: 1. A secure and reliable software-defined information fabric that can collect sensor data (while ensuring privacy), provide computing to extract meaning and devise strategies, and execute control actions in timely fashion; 2. A framework for deploying applications on this fabric; 3. Business-intelligence services that offer analytics, machine learning, and algorithmic support for smart applications. We will demonstrate smart applications in transportation, air quality, buildings, and crowd management in Vaughan, Newmarket, Toronto, and Montreal.x000D