Loom: A Modular Open-Source Approach to Rapidly Produce Sensor, Actuator, Datalogger Systems.
Sensors (Basel)
; 24(11)2024 May 28.
Article
in En
| MEDLINE
| ID: mdl-38894257
ABSTRACT
In the face of rising population, erratic climate, resource depletion, and increased exposure to natural hazards, environmental monitoring is increasingly important. Satellite data form most of our observations of Earth. On-the-ground observations based on in situ sensor systems are crucial for these remote measurements to be dependable. Providing open-source options to rapidly prototype environmental datalogging systems allows quick advancement of research and monitoring programs. This paper introduces Loom, a development environment for low-power Arduino-programmable microcontrollers. Loom accommodates a range of integrated components including sensors, various datalogging formats, internet connectivity (including Wi-Fi and 4G Long Term Evolution (LTE)), radio telemetry, timing mechanisms, debugging information, and power conservation functions. Additionally, Loom includes unique applications for science, technology, engineering, and mathematics (STEM) education. By establishing modular, reconfigurable, and extensible functionality across components, Loom reduces development time for prototyping new systems. Bug fixes and optimizations achieved in one project benefit all projects that use Loom, enhancing efficiency. Although not a one-size-fits-all solution, this approach has empowered a small group of developers to support larger multidisciplinary teams designing diverse environmental sensing applications for water, soil, atmosphere, agriculture, environmental hazards, scientific monitoring, and education. This paper not only outlines the system design but also discusses alternative approaches explored and key decision points in Loom's development.
4G LTE; Arduino; Loom; Maker community; OPEnS; Oregon State University; STEM education; Wi-Fi; agricultural monitoring; atmospheric monitoring; customizable sensors; datalogging; environmental sensing; in situ sensors; internet connectivity; low cost; low power; microprocessors; off-the-shelf sensors; open-source; power conservation; radio telemetry; real-time data; scientific monitoring; soil monitoring; water monitoring
Full text:
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Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Sensors (Basel)
Year:
2024
Document type:
Article