Extended Telemetry Reliability Analysis of a Solar-Powered IoT Smart Irrigation System
DOI:
https://doi.org/10.62535/ak67hc54Keywords:
data quality, Internet of Things, Smart Irrigation, Soil Moisture, solar energyAbstract
This study presents a differentiated reanalysis of telemetry from a stand-alone solar-powered smart irrigation prototype. Instead of repeating the final-project summary, the analysis uses an updated August export containing 602 additional observations and applies continuity, completeness, temporal harmonization, ceiling-aware soil-moisture, and rule-consistency audits. The combined dataset contained 12,025 unique timestamps from 1 July to 9 August 2026. No missing value was interpolated. Sampling gaps greater than 30 minutes formed 42 sessions, while ten core telemetry fields were simultaneously valid in 63.29% of records. The two soil-moisture channels produced 3,819 paired observations and 3,682 paired five-minute bins. The automatic and manual channels reached the 100% ceiling in 71.25% and 46.35% of paired records, respectively; daily median differences were therefore zero percentage points with an interquartile range of 0-6. Across 3,789 valid battery-voltage and Energy Management System code pairs, threshold agreement was 99.60%. After 9 July, panel and battery voltage ranks were strongly associated (rho=0.995), with a median offset of 0.06 V. The extended audit confirms reliable rule classification and closely tracking voltage channels, but it also shows that sensor ceilings, incomplete environmental readings, and absent pump-ON history prevent valid claims about irrigation, water, or energy efficiency.
References
Abdelmoneim, A. A., Al Kalaany, C. M., Khadra, R., Derardja, B., & Dragonetti, G. (2025). Calibration of low-cost capacitive soil moisture sensors for irrigation management applications. Sensors, 25(2), 343. https://doi.org/10.3390/s25020343
Adla, S., Rai, N. K., Karumanchi, S. H., Tripathi, S., Disse, M., & Pande, S. (2020). Laboratory calibration and performance evaluation of low-cost capacitive and very low-cost resistive soil moisture sensors. Sensors, 20(2), 363. https://doi.org/10.3390/s20020363
Al-Ali, A. R., Al Nabulsi, A., Mukhopadhyay, S., Awal, M. S., Fernandes, S., & Ailabouni, K. (2020). IoT-solar energy powered smart farm irrigation system. Journal of Electronic Science and Technology, 17(4), 100017. https://doi.org/10.1016/j.jnlest.2020.100017
Hakim, M. F., Kusuma, W., Su'udi, I., Ridzki, I., Setiawan, A., & Syamsuri, T. U. (2024). IoT-based monitoring system for energy consumption costs from battery supply. Jurnal Rekayasa Elektrika, 20(4), 156-164. https://doi.org/10.17529/jre.v20i4.35237
Nagahage, E. A. A. D., Nagahage, I. S. P., & Fujino, T. (2019). Calibration and validation of a low-cost capacitive moisture sensor to integrate the automated soil moisture monitoring system. Agriculture, 9(7), 141. https://doi.org/10.3390/agriculture9070141
Obaideen, K., Yousef, B. A. A., AlMallahi, M. N., Tan, Y. C., Mahmoud, M., Jaber, H., & Ramadan, M. (2022). An overview of smart irrigation systems using IoT. Energy Nexus, 7, 100124. https://doi.org/10.1016/j.nexus.2022.100124
Prasetyawati, F. Y., Harjunowibowo, D., Fauzi, A., Utomo, B., & Harmanto, D. (2023). Calibration and validation of INA219 as sensor power monitoring system using linear regression. AIUB Journal of Science and Engineering, 22(3), 240-249. https://doi.org/10.53799/ajse.v22i3.595
Ramli, R. M., & Jabbar, W. A. (2022). Design and implementation of solar-powered with IoT-enabled portable irrigation system. Internet of Things and Cyber-Physical Systems, 2, 212-225. https://doi.org/10.1016/j.iotcps.2022.12.002
Satriyo, P., Nasution, I. S., & F'Alia, S. (2024). IoT-enable smart agriculture using multiple sensors for sprinkle irrigation systems. IOP Conference Series: Earth and Environmental Science, 1290, 012027. https://doi.org/10.1088/1755-1315/1290/1/012027
Vallejo-Gomez, D., Osorio, M., & Hincapie, C. A. (2023). Smart irrigation systems in agriculture: A systematic review. Agronomy, 13(2), 342. https://doi.org/10.3390/agronomy13020342
