Data from: TerraGrow: Integrated Platform for Real Time Plant Monitoring and Automated Watering System With IoT And Fuzzy Sugeno Algorithm

Article title TerraGrow : Integrated Platform for Real Time Plant Monitoring and Automated Watering System With IoT And Fuzzy Sugeno Algorithm Authors Prima Wijayakusumaa, Galang Persada Nurani Hakimb, Bin Lia Affiliations a School of Integrated Circuits and Electronics, Beijing Institute of Technology, China b Department of Electrical Engineering, Faculty of Engineering, Universitas Mercu Buana, Indonesia Corresponding author’s email address [email protected] Abstract Global water scarcity, climate variability, and rising input costs increase the need for precise, evidence based irrigation, yet many available systems are proprietary, expensive, and hard to adapt to diverse field conditions. TerraGrow is an open source, low cost platform that fuses real time soil and microclimate telemetry with a Sugeno type fuzzy controller to automate irrigation while keeping workflows transparent and reproducible. The system streams moisture, pH, temperature, and relative humidity to a lightweight IoT dashboard that supports remote supervision, alarms, and manual override, and it enforces practical safety limits on run time and duty cycle to support reliable field use. Bench and pot trials show predictable moisture to signal behavior that supports simple two point, site specific calibration, stable pH measurements across the agronomic range after buffer calibration, small and consistent temperature and humidity offsets relative to a reference instrument, and short repeatable actuation latencies dominated by deliberate settling windows rather than computation or networking. All firmware, configuration guides, wiring maps, and enclosure models are released under permissive licenses to lower barriers to replication and extension by researchers and growers working toward water efficient, climate resilient irrigation. This low-cost, open-source hardware can be reproduced and adapted for precision agriculture applications, particularly in small-scale or rural farming environments. Technical info Fig. 1. End‑to‑end layout of TerraGrow Fig. 2. TerraGrow’s architecture diagram systems Fig. 3. Sensing Unit — (a) Physical assembly and (b) Schematic. Fig. 4. Actuation Unit — (a) Physical assembly and (b) Schematic. (a) The top‑cap hosts U1 adjacent to the DMS board (U2) and DHT11 (S2), with K1 wired to a pump lead and the battery pack B1 providing the supply; the harnesses S1 (moisture) and S3 (pH) continue unchanged from the sensing stage. (b) The schematic highlights a single ESP32 GPIO driving K1, which then routes the pump M1 through the NO contact to the external supply; grounds are commoned at the controller. This layout keeps high‑current paths short and away from the analog front end, minimizing coupling. The firmware translates the fuzzy output into pulse/duty timing for K1 and logs each actuation with a timestamp for audit and tuning. Figure 5. Build wiring overview — physical view. The assembly view shows U1 (ESP32) at the top‑cap, the DHT11 (S2) mounted near the vent, the battery/regulator (B1) feeding the 3.3 V/5 V rails, the DMS board (U2, CD4051) centered for short analog runs to the stake harness (S1 = moisture bundle, S3 = pH bundle), and the relay (K1) driving the submersible pump (M1) through the normally‑open contact. Fig. 6. TerraGrow operation instructions. Fig. 7. Blynk IoT dashboard configurations Figure 8. The proposed pseudocode of TerraGrow Fig. 9. TerraGrow firmware programs flowchart Fig. 10. Bench and field first-run setups. Fig. 11. Soil moisture vs ADC Fig. 12. Temperature and Relative humidity DHT11 vs HTC-2 Fig. 13. pH response to buffer additions