Published on December 27, 2016 by TheLinuxFoundation

Running an Undersea, Robotic Laboratory on a Fixed Energy Budget – Brent Roman, Monterey Bay Aquarium Research Institute

The Environmental Sampler Processor (ESP) performs a variety of chemical and genetic assays on samples it takes directly from its position moored 2 to 30 meters underwater. This Linux controlled “lab in a can” was developed to identify health hazards, such as toxic algae blooms, in hours rather than days or weeks.

Initially, energy consumed by the main microprocessor and radio communications limited the duration of deployments to about 30 days. Fitfully, over the course of the last 10 years, the system’s hardware, software, firmware, and requirements have evolved to reduce energy use such that year long deployments have recently became possible. The greatest energy savings were achieved with a holistic approach that is readily applicable to many other remote (IOT) devices.

About Brent Roman

Like many budding geeks, I became fascinated by computers as a teenager in 80’s, writing games in BASIC. By age 15, I somehow found myself working after school, for $3 hour, in a garage, next to a drill press, writing software in 8085 and Z-80 assembler to control concrete ready-mix plants.

After graduating from the University of California at Santa Cruz, I worked a brief stint at the Santa Cruz Operation (SCO), where I discovered Linux and never looked back.

Since 2000, I’ve been the software part a small, focused team at the Monterey Bay Aquarium Research Institute that fields semi-autonomous robotic instruments for collecting and classifying waterborne microorganisms in real-time.

In 2005, I presented “Embedding Ruby into a Robotic Marine Laboratory” at Rubyconf

In 2013, I gave a talk at ELC entitled “Making Linux do Hard Real-Time”

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2 Comments on "Running an Undersea, Robotic Laboratory on a Fixed Energy Budget – Brent Roman"

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David Kirwan
David Kirwan
4 months 1 day ago

Cheers for uploading was fun to listening to.

Isaak Ryszard
Isaak Ryszard
4 months 2 days ago