UPDATE (Dec. 8, 2015): Read project final reports.

Anyone with a smartphone benefits from the power of sensors that measure location, movement, ambient light, as well as a range of individual social and economic actions. Sensors hold the potential for new techniques, applications, products and services for addressing climate change, issues of water and health and other important environmental challenges. To spur innovation, the Stanford Woods Institute and Stanford Energy 3.0 (formerly the Energy and Environment Affiliates Program) recently announced four winners of seed funding for new research. The funding program, Sensors and Big Data for Solving Environmental Challenges, will award each team up to $70,000 to develop novel solutions and viable business models for sensors and data analytics tailored to environmental challenges.

The proliferation of increasingly affordable and compact sensors in our built and natural environment is producing a wealth of data on a wide range of environmental phenomena. Big data analytics – originally developed for finance and social media – are being used to mine this data, and help people adapt to climate change impacts. The projects selected for funding were chosen for their innovative approaches to environmental challenges, as well as their potential for large-scale deployment and entrepreneurial applications in a range of industries.

“To push forward sensor applications – to improve public health, groundwater characterization and ocean sustainability – Woods and Stanford Energy 3.0 are thrilled to provide these seed grants to Stanford researchers at the cusp of environmental innovation,” said Brian Sharbono, Woods programs manager.

The projects:

Enabling Crowd Sourced Environmental Monitoring

Beth Pruitt, Associate Professor of Mechanical Engineering and, by courtesy, of Molecular and Cellular Physiology; and Thomas Jaramillo, Woods-affiliated Associate Professor of Chemical Engineering

Combining mechanical and chemical engineering with materials chemistry, this project aims to develop sensing chips that act as chemical “noses,” detecting airborne hazardous chemicals and environmental pollutants. The sensors will be targeted to “sniff” for contaminants such as carbon monoxide, sulfates and volatile organic compounds. Fully realized, the sensors could be implanted in smartphones, and collectively monitor a variety of air conditions to provide a first alert for medical and environmental responders, as well as data important to communities regarding longer-term risks.

Deployment of Soot-particulate Sensors in Flue-gas Stacks

Debbie Senesky, Assistant Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering; and Stephen Luby, Professor of Medicine (Infectious Diseases) and Senior Fellow at the Stanford Woods Institute and the Freeman Spogli Institute

Pollution from brick kilns in Bangladesh, especially particulate matter, causes thousands of premature deaths each year. This project will develop an exhaust stack-mounted sensor that can monitor flue and exhaust gasses to help to improve combustion efficiency in kilns and guide regulatory efforts and enforcement. The particulate sensors will be designed to withstand a harsh environment that includes extremely high temperatures, and could be deployed in other soot-generating systems, such as industrial power plants and automotive exhausts.

Advanced Sensors, Wireless Networking, and Data Analysis for Large-Scale Aquifer Characterization and Monitoring

Peter Kitanidis, Professor of Civil and Environmental Engineering; and Thomas Kenny, Professor of Mechanical Engineering

Management of groundwater, a increasingly precious resource in much of the world, is hampered by technology constraints. Traditional methods of aquifer characterization are costly and yield limited quantitative information. This project will develop sensors to more accurately monitor aquifer hydraulic dynamics, such as permeability and storage, and supply-and-demand dynamics, such as responses to changes in pumping and river flow. This information about the current state and properties of the water system can then be used to accurately model groundwater systems for improved management and prediction.

Using Consumer Cameras and Crowdsourcing Data Collection to Monitor Environmental Challenges

Rob Dunbar, W.M. Keck Professor in the School of Earth Sciences and Senior Fellow, by courtesy, at the Stanford Woods Institute; and Brian Wandell, Isaac and Madeline Stein Family Professor and Professor, by courtesy, of Electrical Engineering

Phytoplankton, small floating algae, responsible for more than half of the photosynthetic activity on Earth and, consequently, more than half of Earth’s oxygen production, are disappearing due to global warming. Current data for monitoring phytoplankton concentrations are expensive and time consuming. This project will develop an inexpensive method for monitoring phytoplankton abundance based on the attributes of images captured by consumer cameras.  It will harness the power of social media and data crowdsourcing by creating a free website where people can post their underwater photos. The images that users contribute together with new means to extract meaningful information from the images will improve the ability to estimate phytoplankton abundance at different locations and times, as well as increase social awareness of the importance of oceanic life and the effects of climate change.