CAREER: Ultra Low-Power Embedded Sensors for High-Density Remote Monitoring of Water Quality

University Of Louisville Research Foundation Inc, Louisville KY

Investigators

Abstract

In this five-year proposed CAREER project, newly developed ultra low-power chemical and turbidity sensors will work alongside low-power commercially-available temperature, pressure and flow sensors to provide high-density remote sampling of the watershed environment in eastern Kentucky. Scientific Merit: The scientific goal of this project is to build and use a low-cost sensor platform for real-time water quality monitoring. Original research will be conducted into ultra low-power chemical and turbidity sensors. These micro- and nanofabricated components will be integrated into a macroscale sensor network using off-the-shelf wireless networking hardware and open-source software that has recently become available. Wireless communication nodes will each connect to dozens of low-power submersible sensors at different depths; since depths and sensor types depend on the application, a standard electrical and mechanical sensor interface will allow users to easily customize the network. The end result will be a new set of low-cost research tools available to help environmental and geological researchers ask new scientific questions, backed by the ability to carry out watershed monitoring projects with greater data resolution than ever before. Broader Impact/Educational Activities: Educational activities focus on using the sensor network to monitor water quality in eastern Kentucky. Due to the rugged Appalachian terrain, previous studies of the region's water quality have not been carried out at high resolution. Mining, agriculture, and natural events contribute to both degradation of water quality and changes in the hydrological dynamics of ground and surface water flow, yet the impracticality of accessing a remote streambed during a storm, and the low spatial density of conventional sampling, have made it difficult to pinpoint the source of a change in water quality without after-the-fact laboratory techniques. The broader impact of these remote access real-time water quality maps will be an improved ability to monitor, understand, and mitigate sources of pollution affecting human and ecological communities. Two groups of Kentucky students, one in urban Louisville and another in rural eastern Kentucky, will participate in the project's educational activities. Sensor fabrication and testing will be conducted at the University of Louisville by first-year students in our Introduction to Engineering curriculum. Because this project fits into the larger context of improving the natural environment, it may attract students who have not previously considered majoring in electrical and computer engineering due to unfamiliarity with the purpose and variety of career options in the field. These underrepresented students come disproportionately from the female and minority population. This project will also establish a collaborative link between the engineering school at the University of Louisville and Eastern Kentucky University, which does not have an engineering department. Field testing, data collection, and analysis will be conducted by students at Eastern Kentucky University via the Eastern Kentucky Environmental Research Institute, which was created in 2005 with funds from the National Science Foundation's Experimental Program to Stimulate Competitive Research (NSF-EPSCoR). Its purpose is to foster interdisciplinary research into understanding the effect of environmental function on eastern and central Kentucky's land, air and water, and to encourage both undergraduate and graduate student participation in the design and execution of research projects, particularly field-based research activities. Early in the project, professors, students and community members will specify sensors to best complement the monitoring methods they are currently using. In return, they will obtain new research instruments, and hands-on experience with cutting-edge wireless sensor network technology.