Location: Sustainable Water Management Research
Project Number: 6066-13000-006-044-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Aug 1, 2026
End Date: Sep 30, 2028
Objective:
The overall goal of this project is to enable the more efficient use of groundwater resources which will improve farmer profitability and ensure the longterm health of natural resources in keeping with the research priorities of the Secretary of Agriculture. This project will develop an integrated, secure, and scalable system for Internet of Things (IoT) data acquisition and utilization. Objective 1 will design and develop a prototype token-based software solution capable of securely retrieving data from the most common data loggers used in row crop agricultural production and research and transmitting hose data to a secure and compliant cloud environment compliant with cybersecurity best management practices, including quarantining and scanning data packets before release for processing. Objective 2 will design and implement prototype quality analysis and quality control (QA/QC) software that automatically evaluates incoming data for errors, anomalies, and inconsistencies, generating proposed corrections that are retained as a secondary dataset pending data owner approval. Objective 3 will establish robust structured query language (SQL) database systems capable of storing both raw and QA/QC-adjusted datasets, with configurations optimized to handle large-scale high-frequency data streams from spatially distributed IoT networks. Objective 4 will develop a secure and intuitive user interface that enables researchers to search, visualize, customize, and download data products, incorporating map-based selection, variable filtering and customizable outputs, while also tracking user interactions and maintaining adherence to cybersecurity standards.
Approach:
The project will employ a modular systems engineering approach consisting of four integrated components: secure data acquisition, automated quality assurance and quality control (QA/QC) processing, scalable data storage, and user-centered data access. The data acquisition layer will utilize token-authenticated and encrypted communication protocols to retrieve data from in-field data loggers and sensors and transmit those data to cloud endpoints, where incoming data packets will be quarantined and scanned for security threats prior to ingestion. The QA/QC processing layer will apply rule-based and statistical algorithms to evaluate data completeness, identify outliers or sensor malfunctions, and generate recommended data corrections, preserving both raw and adjusted data for transparency and traceability. The data storage layer will implement efficient structured query language (SQL) database structures optimized for time-series geospatial datasets, enabling rapid querying and integration with analytical tools. The user interface layer will build upon the demonstrated prototype system, providing interactive map-based visualization, region and station selection, customizable variable selection (such as temperature, precipitation, pressure, etc.), and configurable data export options, allowing users to generate tailored datasets and preview outputs prior to download. Collectively, these components will be integrated within a secure cloud environment that complies with federal cybersecurity standards and supports scalable expansion from regional deployments to nationwide coverage.