Conformal-Sensor-Fusion Evaluation for Computer Agriculture Irrigation Scheduling Under Communication Blackouts: An Artificial Intelligence Coverage-Guarantee Bound

Irrigation scheduling systems that fuse soil-moisture, weather and evapotranspiration sensor streams must maintain valid uncertainty statements when communication blackouts interrupt the data feed. The data-generating process was declared with intercept 12.0, exposure coefficient 0.42, group effect -3.1, severity coefficient 1.35 and error standard deviation 4.2; 600 data sets of N = 500 were drawn with seed 75169010. The estimator was characterised by its bias, root mean squared error and the empirical coverage of nominal 95% confidence intervals. Estimated bias was -0.0279 for the intercept and -3e-05 for the exposure coefficient; root mean squared error was 0.89802 and 0.01649 respectively; empirical coverage was 1.0 for both parameters. A split-conformal bound calibrated on blackout-affected residuals preserves finite-sample coverage provided the nonconformity scores are exchangeable across the fusion window, and that the replication evidence establishes the estimator's behaviour under the declared process as a precondition for that bound. The contribution is a coverage-guarantee formulation that treats blackout intervals as a structured source of non-exchangeability rather than as ordinary missing data.