Improving Monitoring and Decision-making with Uncertain Sensor Data

Terrestrial contaminated sites – such as abandoned oilfields, chemical spill sites, or former industrial zones – are a major environmental problem in Canada and around the world. Environmental Material Science has created new environmental monitoring equipment that generates high-resolution spatially and temporally explicit data on environmental quality. The data must be visualized and then used to make decisions regarding if site remediation needs to occur, or if occurring, if site remediation should stop. Such environmental management decisions need to explicitly and transparently community data uncertainty and variability in the decision-making process. Data visualization techniques in the environmental sciences that allow non-expert stakeholders to interpret complex data streams do not exist, with existing techniques designed to be used by experts, who then report to stakeholders. The intent of this research project is to develop data visualization approaches that can be used by non-expert stakeholders to aid in their decision making process on environmental site management.

Intern: 
Natanael Tome
Faculty Supervisor: 
Carl Gutwin
Province: 
Saskatchewan
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