TY - JOUR
T1 - Low-cost electronic sensors for environmental research
T2 - Pitfalls and opportunities
AU - Chan, Kris
AU - Schillereff, Daniel
AU - Baas, Andreas
AU - Chadwick, Michael
AU - Main, Bruce
AU - Mulligan, Mark
AU - O'Shea, Francis
AU - Pearce, Reagan
AU - Smith, Thomas E.l.
AU - Van Soesbergen, Arnout
AU - Tebbs, Emma
AU - Thompson, Joseph V
PY - 2020/9/25
Y1 - 2020/9/25
N2 - Repeat observations underpin our understanding of environmental processes, but financial constraints often limit scientists’ ability to deploy dense networks of conventional commercial instrumentation. Rapid growth in the Internet-Of-Things (IoT) and the maker movement is paving the way for low-cost electronic sensors to transform global environmental monitoring. Accessible and inexpensive sensor construction is also fostering exciting opportunities for citizen science and participatory research. Drawing on 6 years of developmental work with Arduino-based open-source hardware and software, extensive laboratory and field testing, and incorporation of such technology into active research programmes, we outline a series of successes, failures and lessons learned in designing and deploying environmental sensors. Six case studies are presented: a water table depth probe, air and water quality sensors, multi-parameter weather stations, a time-sequencing lake sediment trap, and a sonic anemometer for monitoring sand transport. Schematics, code and purchasing guidance to reproduce our sensors are described in the paper, with detailed build instructions hosted on our King’s College London Geography Environmental Sensors Github repository and the FreeStation project website. We show in each case study that manual design and construction can produce research-grade scientific instrumentation (mean bias error for calibrated sensors –0.04 to 23%) for a fraction of the conventional cost, provided rigorous, sensor-specific calibration and field testing is conducted. In sharing our collective experiences with build-it-yourself environmental monitoring, we intend for this paper to act as a catalyst for physical geographers and the wider environmental science community to begin incorporating low-cost sensor development into their research activities. The capacity to deploy denser sensor networks should ultimately lead to superior environmental monitoring at the local to global scales.
AB - Repeat observations underpin our understanding of environmental processes, but financial constraints often limit scientists’ ability to deploy dense networks of conventional commercial instrumentation. Rapid growth in the Internet-Of-Things (IoT) and the maker movement is paving the way for low-cost electronic sensors to transform global environmental monitoring. Accessible and inexpensive sensor construction is also fostering exciting opportunities for citizen science and participatory research. Drawing on 6 years of developmental work with Arduino-based open-source hardware and software, extensive laboratory and field testing, and incorporation of such technology into active research programmes, we outline a series of successes, failures and lessons learned in designing and deploying environmental sensors. Six case studies are presented: a water table depth probe, air and water quality sensors, multi-parameter weather stations, a time-sequencing lake sediment trap, and a sonic anemometer for monitoring sand transport. Schematics, code and purchasing guidance to reproduce our sensors are described in the paper, with detailed build instructions hosted on our King’s College London Geography Environmental Sensors Github repository and the FreeStation project website. We show in each case study that manual design and construction can produce research-grade scientific instrumentation (mean bias error for calibrated sensors –0.04 to 23%) for a fraction of the conventional cost, provided rigorous, sensor-specific calibration and field testing is conducted. In sharing our collective experiences with build-it-yourself environmental monitoring, we intend for this paper to act as a catalyst for physical geographers and the wider environmental science community to begin incorporating low-cost sensor development into their research activities. The capacity to deploy denser sensor networks should ultimately lead to superior environmental monitoring at the local to global scales.
KW - Arduino
KW - build-it-yourself
KW - data-logging
KW - environmental monitoring
KW - FreeStation
KW - low-cost electronic sensors
KW - microcontrollers
KW - open-source
KW - open-source hardware
UR - http://www.scopus.com/inward/record.url?scp=85091439028&partnerID=8YFLogxK
U2 - 10.1177/0309133320956567
DO - 10.1177/0309133320956567
M3 - Article
AN - SCOPUS:85091439028
SN - 0309-1333
JO - PROGRESS IN PHYSICAL GEOGRAPHY
JF - PROGRESS IN PHYSICAL GEOGRAPHY
ER -