Better Data from Smarter Sensors: Tools, Techniques, and Trends

We are challenged to monitor a growing array of environmental factors in more remote locations, almost always with smaller budgets. Commercial instrumentation, along with adequate calibration, maintenance, and user training... [ view full abstract ]

We are challenged to monitor a growing array of environmental factors in more remote locations, almost always with smaller budgets. Commercial instrumentation, along with adequate calibration, maintenance, and user training can produce impressive results—but at great expense. Open source tools like Arduino and cheap sensors from popular DIY sources promise more affordable and adaptable solutions, yet systems built with these tools and sensors often suffer from terrible accuracy and poor reliability. How can we bridge the gap?

Ken is a Nerds For Nature Organizer and an electronics engineer with considerable experience in both academia and industry. In collaboration with USGS, Creative Commons, and others, he has recently been tackling these issues for several air and water quality sensor projects and will share some insights.

He will start with a brief overview of common low-cost environmental sensors and circuits and will explain why you might not want to use many of them. Conversely, he will present some novel off-the-shelf and DIY sensor options that just might fit your needs. Finally, he will consider how to make individual sensors smarter about themselves and the data they report by using Smart Transducer Interface Modules (STIMs), Transducer Electronic Data Sheets (TEDS), and similar techniques that can improve calibration accuracy and simplify deployment in the field.

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Ken McGary has worked for leading aerospace, telecommunications, and biomedical companies, including General Dynamics, DiCon Fiberoptics, and Allergan-Humphrey Instruments (now Zeiss Meditec), and for over a decade helped neuroscientists develop research apparatus at UC San Francisco. Now he’s focused on designing open source smart sensor circuits and systems that collect higher quality environmental sensor data with lower overall project costs.