As part of the “Enviro-Net: Sensing our Changing Environment ” initiative, this project will aim to demonstrate the use of advanced monitoring tools driven by the development of wireless sensor networks and stream analytics. The goal is to provide real-time environmental monitoring algorithms for state-of-the-art environmental information to industry and government.
The University of Alberta’s cutting-edge, remote-sensing climate research networks provided tremendous volumes of data that scientists evaluated using manual methods, slowing research to a crawl. To acquire insight quickly enough to help policymakers respond effectively with necessary and lasting policy changes, scientists needed a way to aggregate, evaluate and analyze live data streams in real time.
High-speed data collection and IBM InfoSphere Streams analytics allow researchers to analyze more than 10,000 data points per second—hundreds of billions of data points per year—from hundreds of sensors distributed across forest environments under study. The system enables real-time analytics and trend prediction, helping scientists develop conclusions from critical data and produce research that supports prompt responses to critical events.
“We are detecting, visualizing and even predicting subtle changes in the health of ecosystems in real time.”
—Dr. Arturo Sanchez-Azofeifa, professor, researcher and director of the Centre for Earth Observation Sciences
Dr. Arturo Sanchez-Azofeifa (Professor, Earth & Atmospheric Sciences, University of Alberta)
IBM Thomas J. Watson Research Center
Analytics for the Mining & Tailings Environments
The main goal of this collaboration is to extend the use of eddy covariance techniques applied to forest environments into the mining domain. The study will explore the integration of advanced mathematical approaches into IBM’s InfoSphere Streams to estimate real evapotranspiration at drying tailing ponds in northern Alberta.
The focus of this research team is on the development of techniques to estimate real evapotranspiration from drying tailing points, information that is highly needed for water conservation programs by mining companies in Alberta. Drying tailing points are sites where by-products from oil sand production are deposited. These deposits are thin surfaces of sand and other materials that are spread over an area and air-dried. The expectation is that once it is dried, a new layer will be placed on top, dried again, and so forth until enough material has been dried to initiate ecosystem restoration activities. Associated to this process is the time that the thin layer takes to dry so a new one can be placed on top. In general, estimations of the evaporation rates are based on empirical approaches with no real evaluation of true evapotranspiration. As such, providing true evapotranspiration rates will be a significant contribution to mining companies interested on using advanced analytic techniques not yet explored in the mining environment.
Dr. Ward Wilson (Professor, Civil and Environmental Engineering, University of Alberta)
IBM Thomas J. Watson Research Center
Analytics for Water Management
This project between the University of Calgary and IBM focuses on the conceptualization, prioritization and assembly of the key elements of an Intelligent Operations Centre (IOC) that will form the analytic and visualization platform for the Advancing Canadian Wastewater Assets (ACWA) project. This project will begin by expanding on the results of our proof of concept with the demonstration of the organization and utility of the IOC. This will be used to engage new stakeholders and provide access to real-time data. Supporting the goals of the ACWA, the IOC will be used to construct the platform to integrate water management in Alberta beginning with the Bow River Basin.
Dr. Leland Jackson (Professor, and Executive Director (ACWA), University of Calgary)
IBM Software Group, IBM Natural Resources Solution Centre