DETROIT – A team of Wayne State researchers have received an Azure Award – the “AI for Earth” award – from Microsoft for addressing water contamination in Michigan from toxic leaks and superfund sites.
The report is called, “AI for Earth: A Cloud-based Analytics for Real-time Monitoring of Landfills/Superfund Sites and the Adjacent Watershed.”
“Our project will develop an in-situ and real-time, high-resolution and cost-efficient Internet of Things (IoT) sensing network for detecting and monitoring VOCs and SVOCs,” said Yongli Zhang Ph.D., assistant professor of civil and environmental engineering. “We will incorporate IoT sensing networks, machine learning, cloud computing and ESRI’s ArcMap tools to develop an open-source, real-time and cloud-based simulation tool with user-friendly maps, visuals and educational media that will create a comprehensive network for real-time detection and monitoring of water contamination, and improve public awareness of these issues in a timely manner.”
According to the research team led by Zhang, Ph.D., and Weisong Shi, Ph.D., professor of computer science, the various pollutants, volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) from toxic and superfund sites are major concerns due to their multiple pathways for human consumption and exposure – breathing, drinking water, contaminated foods (i.e. fish) and absorption through skin. It is currently difficult to measure and analyze data from sampling methods due to high costs and complexity of current analytical methods.
The Michigan Department of Environmental Quality has estimated that there are approximately 4,000 toxic sites in Michigan that are contaminated due to VOCs and SVOCs, with 65 of them being listed as National Priorities List (NPL) sites. In addition, the metro Detroit area is surrounded by a number of toxic and superfund sites due to heavy contamination caused by hazardous waste that poses a risk to human health and/or the environment.
“To address these critical concerns, we will develop a distributed monitoring network that contains sensors at one superfund site and selected locations of the adjacent watershed as a pilot project to monitor and analyze VOCs and SVOCs in real time by levering our edge computing technique and the AI services provided by Microsoft Cloud,” said Shi. “In addition, we will be able to monitor other environmental and water conditions such as temperature, pH, conductivity and more.”
The results that the Wayne State team collects will help improve water quality and the health of communities around the superfund site. Eventually, the simulation tool will be available to others for monitoring purposes.
In addition to Shi and Zhang, Javad Roostaei, Ph.D. candidate in civil and environmental engineering and master student in computer science at Wayne State, will collaborate on the project.