Environmental Sensing and Monitoring Focus

Environmental Sensing and Monitoring Focus

acoustic research at lake
NEAR Lab Alex and Dr Siderius

Northwest Electromagnetics and Acoustics Research Laboratory (NEAR-Lab)

Modeling and analysis of electromagnetic and acoustic wave phenomenon for development of advanced signal processing techniques. The understanding of wave scattering provides a basis to devise and evaluate advanced signal processing algorithms for applications such as radar, sonar, and biomedical imaging.

students working in Dr. Lipor's lab

Trillium Laboratory

The Lipor Lab focus is on the design and analysis of machine learning algorithms, with an emphasis on adaptive and sequential methods aimed at solving problems in environmental sensing. Applications range from air and water pollution monitoring to geothermal energy prospecting.

Environmental Sensing and Monitoring (ESM) Focus Area

Why ECE at Portland State University?

Most of the leading institutions working in environmental sensing are focused on the environmental, oceanographic, and atmospheric sciences. However, there is a strong movement within environmental sensing towards deployment of large numbers of sensors (and collecting large amounts of data), lowering the cost of sensors (necessary for deploying large numbers), reducing the size of sensors, consuming lower power and performing autonomous (on-board) signal processing and efficient data transmission. These trends are partly driven by advances in big data analytics but also by the increasing availability of unmanned platforms. Both massive sensor deployments and using aerial and underwater unmanned platforms (drones) provide new ways to sense but also place severe restrictions on size, power and communication data rates. The areas of sensor system development, on-board signal processing, controls, communications, and power are all core to Electrical Engineering. At Portland State, we focus on the Electrical Engineering challenges associated with the future of environmental sensing and monitoring. 

Major Societal Challenges

Major societal challenges that impact environmental sensing and monitoring. Engineering responses to these challenges point towards potential Research & Education (R&E) opportunities.

  • Ocean health
  • Estimating marine life abundance
  • Tracking terrestrial wildlife
  • Underwater exploration & mapping
  • Efficient agriculture
  • Clean water access/pollution

Research & Education Tracks

Research and education programs to be developed to address the large-scale societal challenges noted above.  

  • Signal Processing and Machine Learning
  • Electromagnetics and Acoustics
  • Data Analytics
  • Underwater Robotics, Controls
  • Autonomous sensing and instrumentation

Research Objectives

Faculty members with expertise in multiple ESM areas enable PSU to:

  1. Enable an integrated approach to identifying and solving environmental problems (from sensing to decisions)
  2. Enable faculty to develop ESM-related, interdisciplinary, high-impact projects
  3. Create high visibility within research community
  4. Consistently attract a balanced graduate student body in signal processing, instrumentation and related areas

Educational Objectives

A diverse ESM engineering faculty permits the ECE department to offer a wide range of ESM engineering courses, with the following objectives: 

  1. Providing solid fundamentals in remote sensing methods (electromagnetic, acoustic)
  2. Establishing vigorous signal processing and embedded systems MS and PhD tracks
  3. Expanded coursework in fundamentals and applications of machine learning coursework and applications
  4. Developing curriculum on underwater robotics
  5. Emphasizing interdisciplinary curriculum

Research Opportunities

Opportunities exist for both undergraduate and graduate students to participate in ESM faculty research. Please contact a faculty member in our current team listed below to inquire about opportunities.

Current Team

Martin Siderius, Professor and Chair. Acoustics, Signal Processing and Autonomous Vehicles and Sensing
John Lipor, Assistant Professor. Signal Processing & Machine Learning
James McNames, Professor. Signal Processing
Richard Campbell, Associate Professor. RFIC Design
Dan Hammerstrom, Professor Emeritus, Pending. Biologically Inspired Computing Structures
Branimir Pejcinovic, Professor. Microelectronics