DESAIN IOT UNTUK SIMULASI MONITORING MIKROKLIMAT DAN IRIGASI ADAPTIF PADA BUDIDAYA PADI DISTRIK TANAH MIRING, MERAUKE
Abstract
This study proposes an Internet of Things (IoT)–based smart rice farming system for microclimate monitoring and adaptive irrigation. Performance was evaluated through a 20-day simulation reflecting conditions in Tanah Miring District, Waninggap Miraf Village (SP5), Merauke Regency, using 10-minute sampling (2,880 theoretical records). A synthetic dataset was generated in Python (NumPy, Pandas) with diurnal temperature–humidity cycles, heavy rainfall episodes, and soil moisture dynamics driven by rainfall/irrigation accumulation plus a simplified evapotranspiration term. Network impairments (packet loss and latency spikes) were included to assess communication robustness.
The architecture follows a layered perception–network–application model, using MQTT for telemetry and modular backend services (device registry, ingestion, time-series storage, rule engine) connected to a monitoring dashboard. Adaptive irrigation applies threshold rules (θ_low = 0.40; θ_high = 0.52), activates watering for up to 30 minutes, and stops automatically when soil moisture reaches the upper threshold.
Results show 97.22% delivery reliability (2,800/2,880 records), mean end-to-end latency of 2.18 s with P95 of 3.60 s, and 80 irrigation activations totaling 2,400 minutes under 138.62 mm rainfall across 14 events. The design also includes standardized data schemas, structured logging, and retry mechanisms, supporting replication, CI/CD integration, and long-term maintenance at larger field scales. Future work will conduct field trials in SP5 to calibrate sensors, derive growth-stage-specific thresholds, and quantify water-use efficiency against conventional irrigation.
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