Good morning, YLN FM ☀
Sample, uploaded and historical inputs for prototype decision support.
Field at a glance
Input observations and calculated prototype indicators · no live sensors
Sample moisture trend
Static illustration · does not plot uploaded or NASA data
Crop conditions
Sample growing profile · not measured
Prototype irrigation plan
Calculated from input records · verify present conditions
Unvalidated sample rule. Recalculate to inspect the prototype result.
What’s influencing the plan
Key factors in this recommendation
Rainfall outlook FORECAST
Open-Meteo · today and the next six days · separate from NASA POWER historical weather
Not fetched.
Fetch a forecast to review possible rain-related changes.
Daily rainfall = rain + showers, excluding snow. Today is a whole-day estimate, not remaining rainfall. Forecasts are uncertain; no amount is automatically deducted from irrigation. Effective rainfall, infiltration, runoff, root-zone storage and safe timing need local agronomic validation.
Weather data: Open-Meteo · API definitions · CC BY 4.0. Rain + showers are combined here for display.
Soil moisture model TRAINED ML · RESEARCH
24-hour sensor forecast · historical evaluation at Arnesano, Italy · open-field tomato
This model runs in your browser on real held-out farm records. It does not use the selected dashboard crop, coordinates, uploaded CSV or Open-Meteo forecast. It cannot recommend an irrigation amount or predict your field without local validation.
Loading trained model…
Values use the source probe’s 0–100 relative scale, not calibrated volumetric water content. One field and season; sensor faults, missing data and future irrigation limit interpretation. This research result does not change the rule-based irrigation plan.
Data adapted from Adamo et al. (2026), Mendeley Data V2 · CC BY 4.0 · Evaluation details. AISIS filters and aggregates sensor records, trains the model and computes these results.
Bring your field data
Upload validated daily records to update dashboard calculations.
CSV files are processed locally in your browser. Required: date (YYYY-MM-DD), increasing dates, and a measurement with explicit units (e.g. soil_moisture_pct). See README for the schema.
Built to make each drop count.
This prototype uses illustrative sample profiles, local CSV records and optional NASA POWER historical weather. Dashboard rules and equations are not scientifically validated. Open-Meteo provides separate forecast estimates on request. No live sensor is connected. A separately trained soil-moisture model runs historical test cases in the research panel; it does not control the irrigation plan. The separate Python pipeline prepares experimental features; it does not run on upload.