Low-cost electronic sensors for environmental research: Pitfalls and opportunities

Abstract

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.

Design and Application of a Low-Cost, Low- Power, LoRa-GSM, IoT Enabled System for Monitoring of Groundwater Resources With Energy Harvesting Integration

“…The majority of existing environmental applications are based on proprietary conventional commercial WSN apparatuses. Furthermore, there is a global shortage of low-cost, longrange wireless monitoring systems for measuring water table depths [36]. To date, no studies have reported on the use of LoRa-based, low-cost WSN in groundwater table management in Tanzania.…”

“…The system consists of a proprietary data collection unit and an open-source data handling and visualization web application. Furthermore, Chan et al [36] proposed a groundwater observatory model that includes a low-cost probe made with low-cost pressure sensors (NXP MPX5010DP and MS5803-02ba) to measure water table depths. The submersible sensor is housed in a waterproof (aluminum tube) enclosure and a common logger in a separate open to air enclosure sample atmospheric pressure.…”

“…Notably, despite the lower costs and rapid adoption of LCS in various fields, deployment of these solutions in developing countries is uncommon [32], with technical and financial reasons among the barriers preventing wider adoption of LCS on that side of the world [34]. In general, the growing applications of LCS have seen a limited number of studies that provide open data in their reality and do not produce information for scientists and other potential stakeholders [36], [32].…”

“…It has been reported that low-cost sensors have been redesigned to provide more scalable and manageable instrumentation. The redesign of LCS has several advantages, including increased environmental spatial and temporal coverage, lower cost per sensor, and customization to a specific physical setting [36]. The simplicity, accuracy and robustness of these sensors have paved the way for promising alternatives in environmental monitoring [32], [38].…”

Remote sensing of the mountain cryosphere: Current capabilities and future opportunities for research

“…With data transmission via high-gain antennae (e.g. Carvallo et al, 2017) or satellite internet, we hypothesise that low-cost sensors, embedded within an AI framework, could revolutionise mountain glacier monitoring, as it has done in many other geoscience disciplines (Chan et al, 2020). For example, such sensors could include Arduinos or Raspberry Pis (Vujovic and Maksimovic, 2014) that could act as a webcam, capture infrared images at night, detect thermal signatures, record acoustic events, detect ground displacement or tremors from calving, track velocity with GPS, or communicate with satellites for real-time ground-truthing.…”