Loom: A Modular Open-Source Approach to Rapidly Produce Sensor, Actuator, Datalogger Systems.

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.

WeatherChimes: An Open IoT Weather Station and Data Sonification System.

Many people in the United States are disconnected from their environment: urban residents spend 90% of their time indoors inside confined climate-controlled spaces. In addition to being physically separated from the natural environment, much of human understanding of the world's environment is inferred from data collected by satellites orbiting 22,000 miles away. In contrast, in-situ environmental sensor systems are physically accessible, location specific, and essential for correcting and validating weather measurements. However, present options for in-situ systems are mostly limited to expensive, proprietary commercial data loggers with inflexible data access protocols. WeatherChimes is an open-source Arduino-programmable, low-cost hardware and software suite that enables near real-time access to in-situ environmental sensor data (including light, temperature, relative humidity, and soil moisture) anywhere with a WiFi internet connection. Scientists, educators, and artists alike can use this tool to obtain and interact with environmental data in new and innovative ways, as well as collaborate remotely. Transforming data collection processes of environmental sensors into Internet of Things (IoT) compatible formats opens new doors into accessing, understanding, and interacting with natural phenomena. WeatherChimes not only enables users to observe data online, but can also transform data into auditory signals and soundscapes through sonification processes or creative animations using newly-created computer applications. Lab and field tests have confirmed the sensor and online data logging performance of the system. We describe the application of WeatherChimes in an undergraduate Honors College classroom and STEM (Science, Technology, Engineering, and Math) education workshop series in Sitka Alaska, which was used to not only teach about environmental sensors, but to explore how different aspects of our environment are interrelated (e.g. temperature and humidity) through sonification.

Weed Warden: A low-cost weed detection device implemented with spectral triad sensor for agricultural applications.

Controlling weeds is essential for farmers to protect resources and maximize crop yield. Between crops, weeds are typically controlled by applying herbicides or tillage to the entire field. However, these control methods are expensive and can pose environmental risks. Robotic weeding systems are a good solution to minimize environmental impact and save money on herbicides, but they are expensive (>$100,000). The Weed Warden is a low-cost (<$200) plant detection sensor that can be mounted on rovers or tractors. The Weed Warden uses an open source multispectral sensor to detect live vegetation and sends a logic signal that could trigger a weed removal system such as a sprayer or mechanical tillage when vegetation is detected. We evaluate the Normalized Difference Vegetation Index (NDVI), Enhanced Normalized Difference Vegetation Index (ENDVI), and Enhanced Vegetation Index (EVI), for producing a value that, combined with a calibrated threshold, will indicate if there is plant life under the sensor. The Weed Warden system using ENDVI is most consistent at detection, with the ability to discriminate 7.6x7.6 cm vegetation samples from bare soil at sensor heights of 30 and 41 cm from the ground. The Weed Warden is a proof-of-concept component of an alternative system to robotic weeders of fallow fields that could help reduce costs, improve environmental outcomes in agricultural settings, and advance research into fallow field management practices.

Hypnos board: A low-cost all-in-one solution for environment sensor power management, data storage, and task scheduling.

Open source in-situ environmental sensor hardware continues to expand across the globe for a variety of applications. Sensor-management systems typically perform three fundamental tasks: sample sensors at a specified time or period, save data onto retrievable media, and switch power to components on and off in between sample cycles to conserve battery energy and increase field operation time. These tasks are commonly accomplished through integrating separate off-the-shelf components into the desired system such as: power relays, SD card hardware, Real-Time Clocks (RTCs), and coin cell batteries. To enable faster prototyping, the Openly Published Environmental Sensing Lab abstracted all of these requirements into a single printed circuit board (PCB), Hypnos, that can be included in any project to achieve these commonly-required capabilities: powering on and off connected sensors on a schedule and logging collected data to the removable SD card. The hardware is laid out in a "Feather" form factor, a popular configuration in the open-source hardware community, to easily mate with other industry standard products. The onboard RTC acts as an alarm clock that wakes a user-attached microprocessor from low-power sleep modes in between sample cycles. By integrating all these components into a single PCB, we save cost while significantly reducing physical system size. The design as well as a suite of code functions that enable the user to configure all the Hypnos board features are detailed.

High precision zero-friction magnetic dendrometer.

Increasing agricultural demand for freshwater in the face of a changing climate requires improved irrigation management to maximize resource efficiency. Soil water deficits can significantly reduce plant growth and development, directly impacting crop quantity and quality. Dendrometers are a plant-based tool that have shown potential to improve irrigation management in high-value woody perennial crops (e.g., trees and vines). A dendrometer continuously measures small fluctuations in stem diameter; this has been directly correlated to water stress measurements using traditional methods. While plant-based measures of water deficits are considered to be the best measures of water stress, current dendrometer methods are imprecise due to mechanical hysteresis and thermal expansion. The high-precision dendrometer created at the OPEnS Lab alleviates these key failure points using zero-thermal expansion carbon fiber, zero friction via a spring tensioning approach, and a linear magnetic encoder. In-lab tests and field deployments have validated device measurements and the execution of these pivotal qualities. Mass deployment of these automated dendrometers has the potential to provide a continuous record of water stress, providing valuable decision support for irrigation management.

SitkaNet: A low-cost, distributed sensor network for landslide monitoring and study.

Landslides threaten the infrastructure and safety of communities. Soil conditions can predict landslide threat, but the cost and complexity of sensing systems for documenting hazardous conditions across a heterogeneous spatial area prevent widespread utilization. The SitkaNet system is a low-cost, easier to install alternative that allows for numerous sites to be monitored with real-time reporting and expands the accessibility of data-driven landslide forecasting. Using a combination of industry-proven sensors and cheaper alternatives, each SitkaNet node can measure the rainfall, six soil moisture sensors at varying depths, water table, atmospheric pressure, humidity, and temperature at each site for less than one-fifth the cost of existing solutions (<$1000/node). The SitkaNet nodes transmit data wirelessly at five-minute intervals over LoRa network to an Ethernet connected hub instead of more traditional on-site cellular or satellite methods. The node electronics are packaged with 3D printed components in a small waterproof case mounted on a hand-driven well-point utilized for the water level measurement. Each node is intended for operation for more than six months on a lithium-ion battery pack: no solar panel is needed, so amenable to low-light sites. The installation process is streamlined which allows for a node to be installed in less than a day compared to multi-day procedures required by other systems.

Low-cost and precise inline pressure sensor housing and DAQ for use in laboratory experiments.

There are many applications for inline pressure sensors, including fluid flow experiments, sensor field deployments, pumps, and Internet of Things systems. We developed a low-cost (~US$56), open-source, customizable inline pressure sensor system with operational flexibility and simple data logging. Most pressure sensors are expensive, not customizable, specific to a single tubing size, provide only analog readings, have poor stability and precision, or are incomplete without a data logger. These issues limit the usefulness of such hardware. Our system addresses all of these concerns. The customizability of both the hardware and firmware (via options or code modification) allows for the device to be tailored easily to each application. Tubing diameter, adapter dimensions, sensor used, logging behavior, and integration with other systems can be configured with ease. Much of the practicality and configurability of the software and hardware arise from the use of our Loom code and ecosystem. We present experimental data for the flow of a viscous fluid between two parallel plates that shows that sudden changes in fluid properties are not always discernible in static images, but are detectable as pressure signals with our inline pressure sensor.