Location: Agroecosystem Management Research
Project Number: 3042-21660-001-003-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Aug 1, 2023
End Date: Dec 31, 2027
Objective:
The National Measurement and Monitoring Innovations for Environmental and Sustainable Agricultural Systems project was established in Lincoln, NE in FY2023. There is a critical need to modernize ARS research data capture technologies and streamline data collection, integration, analytics, storage, and sharing processes and systems, including expanding the environment and natural resources data we collect and automating the way we capture and process the data. With rapidly evolving Federal data management, access, and cybersecurity policies, ARS requires data technology research that will help equip our scientists with technologies that help them maintain data compliance with those policies while delivering agility, innovation, and relevance. This project will lead the development, assessment, and deployment of high priority, cost effective IoT (Internet of Things) technologies, agricultural data standardization and integration, big data tools and analytics for greenhouse gas (GHG) flux measurement and monitoring, environmental feedback, and data-driven agricultural decision-making. The project will innovate data automation, integration, and visualization through operational leadership of the USDA ARS Partnerships for Data Innovations (PDI). This is envisioned as a data science and technology project delivering novel cost-effective sensors and process and data integration innovations. This will be a highly collaborative project with researchers, technicians, and data managers across ARS research units and our university partners. This specific agreement covers our collaborative work with North Dakota State University (NDSU).
Approach:
This project will focus on developing and operationalizing a semi-automated IoT QA/QC software system and expanding a standardized suite of low-cost senor and datalogging technologies. Specifically, this collaboration will develop, integrate and test cloud-based software tools that will process incoming data streams from IoT devices deployed in the field. The software will flag data that is determined to be potentially erroneous. A user interface will be developed to present this data for review by the “owners” of the sensors and options provided for action to take on the questionable data. This collaboration will also complete an engineering evaluation of sensors and/or datalogging technologies provided by the ARS project team. This includes providing a report with results and conclusions from the evaluation to guide future development and deployment of the technology for large scale deployment across ARS research locations. It is expected that two sensor systems will be evaluated in the year 1 effort.
