Open source in-situ environmental sensor hardware continues to expand across the geosphere to a variety of applications. These systems typically perform three fundamental tasks: sample sensors at a specified time or period, save data onto retrievable media, switch power to components on and off in between sample cycles to conserve battery energy and increase field operation time. This is 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 PCB that can be dropped into any project to achieve these commonly-required capabilities. 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 micro controller 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. For more information, please visit open-sensing.org/projects.

Increasing agricultural demand for fresh water resources in the face of a changing climate requires improved irrigation management solutions to maximize resource efficiency while maintaining crop yield and quality. Soil water deficits can significantly reduce plant growth and development, dictating the quantity and quality of the crop. While plant-based measures of water deficits are considered to be the best measures of water stress, current methods for achieving precise stress measurements are time-consuming and inefficient. Dendrometers are one plant-based tool that have shown potential to improve irrigation management in high-value woody perennial crops. High-precision dendrometers continuously measure small fluctuations (± 1 micron) in stem diameter throughout the day, which directly correlates to water stress. However, currently available dendrometers are expensive, have mechanical hysteresis, and are subject to mechanical and environmental issues such as material expansion; weather and animal disruptions; and bulky, invasive design. The dendrometer created at the OPEnS Lab - tailored for grapevines - alleviates these key failure points through the use of zero-thermal expansion carbon fiber, spring tension, and a linear magnetic encoder. The design is also significantly less expensive than that of the competition, costing around $200 as opposed to $1000. Mass deployment of these automated dendrometers has the potential to provide a continuous picture of vineyard water stress at the whole-block level, thus providing valuable decision support for vineyard irrigation management. Follow the project at open-sensing.org/projects.

Reliable, accurate, and affordable linear motion systems for agricultural applications are currently not easily accessible due to their elevated cost. Most systems available to the public have price tags in the thousands and their dimensions cannot be easily customized. Current systems have a max length of about ten meters and for a typical greenhouse application, the length may not be sufficient. The price of the system increases with an increase in length and with a base price in the thousands it becomes almost impractical to buy a system for such application. The HyperRail is a modular linear motion system with a repeatability of 2mm and current top speed of 100mm/s. An advantage this system has is its ability to increase or decrease the length of system with minimum effort and nominal increase in price. The HyperRail can be mounted on a set of tripods or directly on the structure of a building such as a greenhouse. The base price for a three-meter system, on tripods, is US$240 and an additional US$45 for each additional one-and-a-half meter. The HyperRail was designed for the use of hyperspectral imaging but can be adapted for other sensor systems. We report on a nine-meter study over pine seedlings infected with a virus. A push-broom hyperspectral camera (Headwall Nano) was mounted on the carriage of the system imaging the seedlings. The rail is currently being adapted to an environmental sensor suite that will monitor CO2, luminosity, humidity, temperature, and the concentration of dust. The HyperRail also includes bidirectional-wireless communication between the drive and the carriage; this means that the sensor suite can operate autonomously and communicate to the HyperRail drive to move to a specific location and take measurements. This system includes a graphical user interface for users who are unfamiliar with programming but could also be used through a command line interface for individuals that want to work the code and see the effects of the changes immediately. This system was developed at Oregon State University’s OPEnS Lab, here is a link to the project page for more detailed information. URL for project page: http://www.open-sensing.org/hyper-rail/

A system capable of reliably detecting catastrophic landslides and centimeter movement in land mass could save lives and offers landowners valuable information about gradual changes in soil displacement on their land. With precise acceleration and relative positioning data collected from an accelerometer and a set of GPS receivers, a system can be designed to detect subtle changes in sensor position due to land movement. With the rapid production of new microprocessors and greater memory storage capabilities the limits of microcontroller systems are continually expanding. The Slide Sentinel project offers landowners a low-cost alternative to commercial equipment consisting of a network of remote low power sensors that detect fast linear slides and eventually lower soil movements such as creep. Long range low-power (LoRa) radio connections on these sensor nodes wirelessly transmit three-dimensional acceleration, Real Time Kinematic (RTK) GPS coordinates, and sudden shift alerts to a common base station where they are exported to an online spreadsheet to be processed remotely.

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. While plant-based measures of water deficits are the best indication of water stress, current dendrometers 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. The device achieves 0.5-micron resolution, and thermal fluctuations are less than 1 micron over diurnal swings of 25°C. The cost of the device varies with build quantity; parts are $200 - $450 each and assembly requires 6 to 12 hours per system. Dendrometers are currently being deployed with telemetry based on LoRa, which is under evaluation. Without solar charging and telemetry, the battery is sufficient for over two years of operation. Mass deployment of these automated dendrometers has the potential to provide a continuous record of water stress driven changes in stems, providing valuable decision support for irrigation management.

Organisms leave traces of DNA as they move through their environments. The extraction of these DNA traces is known as environmental DNA (eDNA). eDNA provides scientists and researchers a non-invasive, rapid, cost-effective and sensitive way to detect and quantify species. Traditional eDNA sampling consists of manually filtering water, which is labor and cost-intensive for remote locations. Furthermore, commercialized solutions are expensive and require a field operator. This eDNA sampler project aims to provide an affordable, open-sourced, remotely deployable, fully automated, and customizable alternative. The PolyWAG (Water Acquired Genomics) system can run up to 24 inline filter units with support for different conditions including pressure, time and volume limit. The pumps deliver maximum 400mL/min with solenoid valves separating each inline filter to minimize cross-contamination. At the end of each sample, the desired stabilizing solution can be injected to fully submerge the filter for preservation. An optional river depth sensor can provide a proxy for flow to correct eDNA concentrations to allow for improved quantification of organisms. Data acquired during operation including water depth, pressure, temperature, and flow rate will be stored on microSD card in CSV format, which allows easier data export and analysis. A web application provides an intuitive UI for in-field programming, real-time sensor updates, scheduling tasks, and manual operations. We present data from multiple tests showing the length of the preservation period and the contamination level between samples. The PolyWAG system is estimated to be $3000 each, with add-on river depth sensor and 10ah 12V battery.

Currently available soil volumetric water content (VWC) sensors have several drawbacks that pose certain challenges for implementation on large scale for farms. Such issues include cost, scalability, maintenance, wires running through fields, and single-spot resolution. The development of a passive soil moisture sensing system utilizing Radio Frequency Identification (RFID) would allay many of these issues. The type of passive RFID tags discussed in this paper currently cost between 8 to 15 cents retail per tag when purchased in bulk. An incredibly cheap, scalable, low-maintenance, wireless, high-resolution system for sensing soil moisture would be possible if such tags were introduced into the agricultural world. This paper discusses both the use cases as well as examines one implementation of the tags. In 2015, RFID tag manufacturer SmarTrac started selling RFID moisture sensing tags for use in the automotive industry to detect leaks during quality assurance. We place those tags in soil at a depth of 4 inches and compared the moisture levels sensed by the RFID tags with the relative permittivity (εr) of the soil as measured by an industry-standard probe. Using an equation derived by Topp et al, we converted to VWC. We tested this over a wide range of moisture conditions and found a statistically significant, correlational relationship between the sensor values from the RFID tags and the probe’s measurement of εr. We also identified a possible function for mapping vales from the RFID tag to the probe bounded by a reasonable margin of error.

Reliable automatic water samplers allow repetitive sampling of various water sources over long periods of time without requiring a researcher on site, reducing human error as well as the monetary and time costs of traveling to the field, particularly when the scale of the sample period is hours or days. The high fixed cost of buying a commercial sampler with little customizability can be a barrier to research requiring repetitive samples, such as the analysis of septic water pre- and post-treatment. DIY automatic samplers proposed in the past sacrifice maximum volume, customizability, or scope of applications, among other features, in exchange for a lower net cost. The purpose of this project was to develop a low-cost, highly customizable, robust water sampler that is capable of sampling many sources of water for various analytes. A lightweight aluminum-extrusion frame was designed and assembled, chosen for its mounting system, strength, and low cost. Water is drawn from two peristaltic pumps through silicone tubing and directed into 24 foil-lined 250mL bags using solenoid valves. A programmable Arduino Uno microcontroller connected to a circuit board communicates with a battery operated real-time clock, initiating sampling stages. Period and volume settings are programmable in-field by the user via serial commands. The OPEnSampler is an open design, allowing the user to decide what components to use and the modular theme of the frame allows fast mounting of new manufactured or 3D printed components. The 24-bag system weighs less than 10kg and the material cost is under $450. Up to 6L of sample water can be drawn at a rate of 100mL/minute in either direction. Faster flowrates are achieved by using more powerful peristaltic pumps. Future design changes could allow a greater maximum volume by filling the unused space with more containers and adding GSM communications to send real time status information.

Advancements in sensing technology have sparked a new age of data acquisition and transmission that continue to change the way we understand the world around us. In earth science, we often must move and store tremendous amounts of data from remote locations. Present options are limited to costly propriety devices, which are rigid in structure and have numerous expenses associated with their use. The solution developed in the Openly Published Environmental Sensing Lab (OPEnS) at Oregon State University, was to employ a new methodology using low-power, open-source hardware, and software, to achieve near-real-time data logging from the field to the web. This new approach simultaneously lowers the cost of experimentation and data collection and breaks down traditional technical barriers. Data can be collected remotely from nearly anywhere on Earth using a decentralized OPEnS Hub which can utilize a host of low bandwidth transmission protocols and modes of communication, such as: 900 MHz Long Range Radio (LoRa) with a transmission distance of up to 25 km, the Global System for Mobile communications (GSM) using well established cell network infrastructure, Wi-Fi for high bandwidth applications, and Ethernet where LAN connections are available. It is notable that LoRa technology is still developing and has been expanded to transmit to an ever-growing constellation of satellites, making this technology truly global in its applicability. The OPEnS-Hub is capable of mesh networking with other nodes and will parse and back up the data to an onboard microSD card. By first exploiting a free open-sourced Application Programming Interface (API), PushingBox, acting as a data broker, and secondly, a customized Google App script, the OPEnS-Hub was able to achieve a dynamic, low latency portal connecting to google sheets. These methods working in tandem allowed for near real-time data logging of over a dozen devices each with unique sensor suites to form valuable time series data. This poster details our methods and evaluates the application and development of PushingBox’s API, Google App Script, Adafruit’s open-hardware Feather development boards, the Hypertext Transfer Protocol (HTTP) and various modes of data communication used to collect nearly half a million data points dispersed across remotes sites in the state of Oregon to date.

Sap flux probes have been used to study sap velocity since the early 20th century and have progressively improved in accuracy and usability. Advances are also being made in making these devices cheaper via open-sourced projects; however, these solutions require extensive time and skill to construct a reliable device. When our lab tried to replicate Miner’s results, only two of the first ten probes built passed rudimentary testing. We therefore redesigned the system in a PCB-based design that simplifies construction, and presents opportunity for automated mass manufacturability at a scale not possible with existing designs. New designs for both the Thermal Dissipation Method (TDM) and the Heat Ratio Method (HRM) techniques were tested. We present our open-source designs for wireless sap flux probes that communicate over 2km using the LoRa protocol through canopy to an internet hub, where data is logged in near-real-time and accessible online.

Increased demand for precision agriculture is reflected by a global rise in greenhouse food production. To maximize crop efficiency and yield, commercial greenhouses require live monitoring of growth conditions. Recent advances in open-source hardware allow for environmental sensing with the potential to rival lab-grade equipment at a fraction of the cost. This study introduces a high-resolution sensor package that costs less than $400. Consisting of microcontrollers and small open-source hardware, the sensor package can be deployed on the HyperRail, a modular conveyance system developed in Oregon State University’s OPEnS Lab. The system can then provide data from multiple sensing locations at the cost of a single package. Sensor data, including CO2, temperature, relative humidity, luminosity and dust/pollen, is saved to a microSD card as the HyperRail-mounted package travels throughout the greenhouse. A wireless GFSK nRF connection to a network hub allows the broadcast of a live stream of environmental conditions online. CO2 monitoring efforts are especially relevant to greenhouse management as artificially elevated levels can significantly increase plant growth. Results from calibration in the lab show that the K30 CO2 sensor ($85) can be calibrated to be accurate within less than 10 ppm of industry standard equipment costing up to $10,000. Our sensor package’s instructions, code, wiring, and 3D-printed enclosures are openly-published on GitHub. Addition of an RFID tag soil moisture sensing system is anticipated. Actuators may also be integrated in the future, allowing the system to automatically adjust greenhouse controls (i.e. CO2, water) in response to sensor readings. The affordability of this package can make precision agriculture more accessible in developing countries where conventional monitoring systems are not feasible. Efficient use of resources and the ability to adapt to local challenges with input from the open-source community has the potential to improve global crop yield.

The Smart Rock is a submersible sensor suite that monitors temperature, pressure (water depth), turbidity, and electrical conductivity. The sensor suite can be deployed in streams for 3-6 months at a time taking data every 20 minutes. The frequency of data collection can be changed which will affect battery life. Smart Rock assembly has been streamlined to make assembly and programming as accessible as possible. We want water sensing to be affordable and accessible to water scientists around the world. Our goal with the Smart Rock remains to develop an affordable, user friendly, low cost, and accessible for our different users needs. For those familiar with previous versions of the Smart Rock let me cover what has changed with this latest revision. We have designed our own electrical conductivity sensor with increased control for the user to change the range and resolution of the sensor. The enclosure has shrunk with a new selection of batteries doubling the capacity of the previous version’s battery. We worked on stabilizing the code and simplifying the operation. You can now control the unit’s settings via a config file on the SD card. No more Arduino reprogramming to change settings.