Automatic Monitoring of Class A Pan Evaporation using the Internet of Things (IoT)
DOI:
https://doi.org/10.58915/aset.v3i.586Abstract
This study aimed to assess suitable water level sensor types and implement the automated monitoring of water levels within a Class A pan evaporation system using the Internet of Things (IoT). Both analogue and ultrasonic water level sensors underwent testing in controlled laboratory conditions for performance analysis. The results showed that the analogue water level sensor exhibited suboptimal output sensor responses compared to the ultrasonic sensor, primarily due to its susceptibility to variations in solution types and immersion depths. In contrast, ultrasonic sensors demonstrated strong performance with acceptable error rates, as evidenced by the Mean Absolute Error (MAE) of 1.03, Root Mean Squared Error (RMSE) of 1.42, and Coefficient of Determination (R²) of 0.94 during laboratory testing. However, the ultrasonic sensor's performance was somewhat reduced during field testing, exhibiting accuracy levels ranging from 6.7% to 51.2% within a greenhouse environment during rock melon cultivation. These discoveries highlight the feasibility of using ultrasonic sensors with environmental calibration to automate real-time evaporation measurements towards precision irrigation practices.
Keywords:
Ultrasonic sensor, Water level, Internet of Things, Precision irrigation, EvaporationReferences
Bhatnagar, V., & Chandra, R. Internet of Things: A Conceptual Visualization. In Smart Agricultural Services Using Deep Learning, Big Data, and IoT, (2021) pp. 81-112.
Nawaz, M. A., Rasool, R. M., Kausar, M., Usman, A., Bukht, T. F. N., Ahmad, R., & Jaleel, A. Plant disease detection using internet of thing (IoT). International Journal of Advanced Computer Science and Applications, vol 11, issue 1 (2020).
Zawawi, M. A. M., Jusoh, M. F., Muhammad, M., Naher, L., Latif, N. S. A., Muttalib, M. F. A., ... & Nugroho, A. P. Knowledge Mapping Trends of Internet of Things (IoT) in Plant Disease and Insect Pest Study: A Visual Analysis. Pertanika Journal of Science & Technology, vol 31, issue 4 (2023).
Gloria, A., Dionisio, C., Simões, G., Cardoso, J., & Sebastião, P. Water management for sustainable irrigation systems using internet-of-things. Sensors, vol 20, issue 5 (2020) p. 1402.
Hamdi, M., Rehman, A., Alghamdi, A., Nizamani, M. A., Missen, M. M. S., & Memon, M. A. Internet of Things (IoT) Based Water Irrigation System. International Journal of Online & Biomedical Engineering, vol 17, issue 5 (2021).
Amassmir, S., Tkatek, S., Abdoun, O., & Abouchabaka, J. An intelligent irrigation system based on internet of things (IoT) to minimize water loss. Indonesian Journal of Electrical Engineering and Computer Science, vol 25, issue 1 (2022) pp. 504-510.
Abdelmoamen Ahmed, A., Al Omari, S., Awal, R., Fares, A., & Chouikha, M. A distributed system for supporting smart irrigation using Internet of Things technology. Engineering Reports, vol 3, issue 7 (2021) p. e12352.
Jusoh, M. F., Muttalib, M. F. A., Krishnan, K. T., & Katimon, A. An overview of the internet of things (IoT) and irrigation approach through bibliometric analysis. In IOP Conference Series: Earth and Environmental Science, vol 756, issue 1 (2021) p. 012041.
Gallardo, M., Elia, A., & Thompson, R. B. Decision support systems and models for aiding irrigation and nutrient management of vegetable crops. Agricultural Water Management, vol 240, (2020) p. 106209.
King, B. A., & Shellie, K. C. A crop water stress index based internet of things decision support system for precision irrigation of wine grape. Smart Agricultural Technology, vol 4, (2023) p. 100202.
Cherqui, F., James, R., Poelsma, P., Burns, M. J., Szota, C., Fletcher, T., & Bertrand-Krajewski, J. L. A platform and protocol to standardize the test and selection low-cost sensors for water level monitoring. H2 Open Journal, vol 3, issue 1 (2020) pp. 437-456.
Burnett, R., Understanding How Ultrasonic Sensors Work | MaxBotix Inc., MaxBotix, (2020). https://www.maxbotix.com/articles/how-ultrasonic-sensors-work.htm
Mohammed, S. L., Al-Naji, A., Farjo, M. M., & Chahl, J. Highly accurate water level measurement system using a microcontroller and an ultrasonic sensor. In IOP Conference Series: Materials Science and Engineering, vol 518, issue 4 (2019) p. 042025.
Bello, M. I., Gana, S. M., Faruk, M. I., & Umar, M. J. Autonomous ultrasonic based water level detection and control system. Nigerian Journal of Technology, vol 37, issue 2 (2018) pp. 508-513.
Pawar, S. D., Rao, D. D., and Lokhande, S., Water Level Monitoring System Using IoT, International Journal of Renewable Energy Exchange, vol 10, issue 11 (2022).
Sharif, S., Statistics for Non-Statistician: Basic Guide to SPSS, 2nd ed. Kedah, Malaysia: Khazanah Darul Aman, (2019).
Hidayat, M. R., Sambasri, S., Fitriansyah, F., Charisma, A., & Iskandar, H. R. Soft water tank level monitoring system using ultrasonic HC-SR04 sensor based on ATMega 328 microcontroller. In 2019 IEEE 5th International Conference on Wireless and Telematics (ICWT), (2019) pp. 1-4.
Dadheech, P., Kumar, A., Singh, V., Raja, L., & Poonia, R. C. A neural network-based approach for pest detection and control in modern agriculture using internet of things. In Smart agricultural services using deep learning, big data, and IoT, (2021) pp. 1-31.
Al-agele, H. A., Jashami, H., & Higgins, C. W. Evaluation of novel ultrasonic sensor actuated nozzle in center pivot irrigation systems. Agricultural Water Management, vol 262, (2022) p.107436.
Fisher, D. K., & Sui, R. An inexpensive open-source ultrasonic sensing system for monitoring liquid levels. Agricultural Engineering International: CIGR Journal, vol 15, issue 4 (2013) pp. 328-334.
