Our oceans are dirty. AI-powered robot microscopes may save them.

In five years, small autonomous AI microscopes, networked in the cloud and deployed around the world, will continually monitor the condition of the natural resource most critical to our survival: water.

 

Our oceans are dirty. AI-powered robot microscopes may save them.

In five years, small autonomous AI microscopes, networked in the cloud and deployed around the world, will continually monitor the condition of the natural resource most critical to our survival: water.

 

Real-time oceanic data is elusive

By 2025, more than half of the world’s population will be living in water-stressed areas. But scientists struggle to collect and analyze even the most fundamental data about the real-time conditions of our oceans, lakes and rivers. There are specialized sensors that can be deployed to detect specific chemicals and conditions in water, but they miss unanticipated ones, like invasive species or the introduction of new chemicals from run off.

Plankton, however, are natural, biological sensors of aquatic health. Even slight changes in water quality affect their behavior. They also form the foundation of the oceanic food chain, which serves as the primary source of protein for more than a billion people. Yet very little is known about how plankton behave in their natural habitat, because studying them typically requires collecting samples and shipping them to a laboratory.

Challenges facing us today

airplane icon

More than half of the world’s population will be living in water-stressed areas within 10 years.

medical icon

Scientists struggle to collect and analyze even the most fundamental data about the real-time water conditions.

global finance icon

Existing data collection is specialized and misses unanticipated events like invasive species.

shoe icon

Very little is known about plankton behavior in their natural habitat.

Live presentation

IBM researcher Tom Zimmerman discusses his work on building small, autonomous 3D microscopes that can be placed in bodies of water to use plankton as an environmental sensor network.

 

Live presentation

IBM researcher Tom Zimmerman discusses his work on building small, autonomous 3D microscopes that can be placed in bodies of water to use plankton as an environmental sensor network.

 

Creating a real-time network of 3D microscopes

IBM researchers are building small, autonomous microscopes that can be placed in bodies of water to monitor plankton in situ, identifying different species and tracking their movement in three dimensions. The findings can be used to better understand their behavior, such as how they respond to changes to their environment caused by everything from temperature to oil spills to run off. They could even be used to predict threats to our water supply, like red tides.

Plot animation of plankton swimming in 3D as observed by IBM's autonomous microscope

In the future, the microscope could be outfitted with high performance, low power AI technology to analyze and interpret the data locally, reporting any abnormalities in real-time so they can be acted upon immediately.

About the microscope

The microscope has no lens and relies on an imager chip, like the one in any cell phone, to capture the shadow of the plankton as it swims over the chip, generating a digital sample of its health, without the need for focusing.

 

About the microscope

The microscope has no lens and relies on an imager chip, like the one in any cell phone, to capture the shadow of the plankton as it swims over the chip, generating a digital sample of its health, without the need for focusing.

 

Tom Zimmerman | Master Inventor @ IBM Research

Illustration of the AI-powered robot microscope

Predictions

IBM 5 in 5 predictions