Los Alamos National Laboratory is applying its combined expertise in data collection, hydro-meteorological data analysis, wireless sensor temperature monitoring, edge-to-cloud data monitoring capabilities, and machine learning to assist area farmers’ efforts to monitor, predict, and mitigate crop-damaging frost events in northern New Mexico site. The work involves:
- Analyzing temperature distribution and vulnerabilities to frost across farm sites, and attempting to identify sources of cold air using drone-based observations and/or data driven models.
- Investigating machine-learning models for processing collected data for temperature and frost prediction.
- Applying machine-learning models and algorithms in the Cloud-HOsted Real-time Data Services (CHORDS) online web application system for real-time testing of temperature and frost predictions.
- Investigating and, if feasible within time and funding constraints, implementing improvements for strengthening Wi-Fi signal at farms.
- Continuing bud-frost experiments performed in previous years by re-examining peach, apricot and cherry bud response to cold temperatures in an experimental setting. Expand this work to apple and grape buds, pending feasibility and time constraints.