Custom Data Logger for Real-Time Remote Field Data Collections

17AERP10_10

10/01/2017

Abstract
Content

Compact, energy efficient instruments have the same functionality as a personal computer.

Army Engineer Research and Development Center, Vicksburg, Mississippi

The U.S. Army Corps of Engineers (USACE), CHL, FRF, had a need for a remote real-time data collection system to control instruments and log and communicate data from five observing stations in the Currituck Sound Estuary, NC1. These stations, referred to as the Currituck Sound Array (CSA), collect a suite of meteorological and oceanographic data including wind, air temperature, humidity, incoming solar radiation (above and below water), waves, currents, water level, salinity, and water temperature, as well as turbidity and many other water quality parameters. This array of instruments has a variety of control commands, sample routines, and output data formats. Additionally, the CSA was designed to act as a natural laboratory for estuarine research and as an instrument and model test bed. These capabilities required a reliable and flexible system that would allow easy modification of sampling schemes, the ability to log as many as 15 instruments with a single logger, and allow the incorporation of additional and novel instrumentation with minimal effort and expense.

The custom loggers were built upon single board computers (SBC) running the Linux operating system. They effectively have the same functionality as a personal computer, overcoming many of the limitations of off-the-shelf loggers. Additionally, off-the-shelf loggers typically operate on a very limited set of commands. These custom Linux-based loggers have a much more diverse and powerful selection of commands, overcoming many of the unique challenges of real-time data collection with robust code and programmatic “watchdogs” that can automatically make sure the logger, instruments, and communications are operating as intended.

Meta TagsDetails
Pages
2
Citation
"Custom Data Logger for Real-Time Remote Field Data Collections," Mobility Engineering, October 1, 2017.
Additional Details
Publisher
Published
Oct 1, 2017
Product Code
17AERP10_10
Content Type
Magazine Article
Language
English