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 Wijayakusuma^a, Galang Persada Nurani Hakim^b, Bin Li^a 

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 

3820251033@bit.edu.cn

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