AgTech Platform & Environmental
Each plot, measured in real time.
Kurvia integrates field sensors, time series, threshold alerts, and satellite imagery into a single operational dashboard. The curve for each variable—humidity, temperature, pH, conductivity, radiation—shifts from being a mere data point to becoming a management decision.
What is
Agricultural and environmental organizations are already generating data: weather stations, soil probes, irrigation telemetry, and public satellite imagery. The problem isn't measurement; it is viewing the measured data together. Kurvia takes these sources, normalizes them by plot, and converts them into actionable indicators, curves, and alerts.
Ingestion of IoT sensor measurements with range validation and gap detection. The status of each variable is determined against its defined operating window.
Sentinel-2 scenes clipped to each plot's polygon, selected by date and cloud cover, reading directly from the Cloud-Optimized GeoTIFF.
Any deviation above or below the range triggers an alert with context: sensor, plot, value, unit, and the exact time of the event.
The platform
Kurvia can be deployed in its entirety or in modules, depending on each organization's level of maturity. All versions share the same model of plots, sensors, and series, meaning that adding a new source does not require rebuilding the dashboard.
Logging of devices, units, and operating ranges: soil moisture and temperature, pH, electrical conductivity, ambient temperature, solar radiation, and irrigation tank levels.
Dashboard featuring comparable curves across sensors and plots, with valid range bands, period-based aggregations, and light/dark modes for field and office use.
Threshold engine that evaluates each incoming measurement and consolidates the history of recent deviations into a single dashboard, sorted by criticality and time.
Inventory of cultivated plots with associated polygons, and automatic satellite clipping from public STAC catalogs, without downloading the full scene.
Classification of plots, crops, and variables into categories and subcategories specific to each organization: the foundation for reports that allow for year-over-year comparisons.
REST API for plots, time series, and satellite scenes, designed to feed agricultural management systems, institutional dashboards, or proprietary prediction models.
How it works
A short, auditable process—with no data lost between spreadsheets and devices that only communicate with their own apps.
Soil and weather sensors send time-stamped measurements. Kurvia validates them against the operating range of each variable.
Each measurement is associated with its plot, crop, and unit. The series are comparable across devices and seasons.
The latest satellite image of the polygon—filtered for cloud cover—is added to compare the point data with the surface data.
Indicators, curves, and alerts reach the field manager with the necessary context to irrigate, fertilize, or intervene.
Architecture
Kurvia relies on open geospatial data standards and Sofis Solutions' engineering practices: documented APIs, cloud or on-premises deployment, and end-to-end traceability.
Where it applies
The same platform serves both the producer who needs to make an irrigation decision and the agency that requires territorial evidence for public policy.
Soil moisture and temperature monitoring by plot for soybean, corn, and wheat, with season-over-season comparisons.
Reservoir levels, consumption, and early deficit alerts to optimize the use of available water.
Territorial monitoring using open data, aggregated indicators, and evidence for rural development programs.
Monitoring of soil and climate variables in sensitive areas, with an auditable history and deviation reporting.
We coordinate a demo using sample data and evaluate together the sensors, plots, and integrations your operation currently has. You can have your first production dashboard up and running in just a few weeks.