Optimizing Agricultural Irrigation in Arequipa - Peru, Through an IoT-Enable Automated Sprinkler Irrigation System

International Journal of Electrical and Electronics Engineering
© 2024 by SSRG - IJEEE Journal
Volume 11 Issue 8
Year of Publication : 2024
Authors : Boulmer Coaguila Aquise, Gidel William Luque Lopez, Jorge Eduardo Zevallos Meza, Jesús Talavera S
pdf
How to Cite?

Boulmer Coaguila Aquise, Gidel William Luque Lopez, Jorge Eduardo Zevallos Meza, Jesús Talavera S, "Optimizing Agricultural Irrigation in Arequipa - Peru, Through an IoT-Enable Automated Sprinkler Irrigation System," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 8, pp. 256-263, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I8P123

Abstract:

The Arequipa region in Peru has challenges in agricultural water management due to the erroneous use of water for irrigation and fluctuating climatic features. This research work describes the design and testing of an IoT-based automated sprinkler irrigation system that was developed with the view to facilitate the efficient use of water in irrigation and boost agricultural yield in the area. The system employs a Raspberry Pi 4B as the principal microcontroller board, which communicates with the soil moisture sensors, temperature and humidity sensors, and weather tickers that track the climate parameters in real-time. The collected sensor data is transferred to a Wi-Fi network that stores data in a cloud, provides farmers with the history of data analysis, and grants them the ability to manually control this system through a web or mobile application. The automated system turns on sprinklers when the soil moisture level reaches certain levels and thus cuts on water usage while making the crops healthier. Some of the benefits obtained during the field trials were that they were able to use 30% less water and get 12% more crop yield than with conventional irrigation methods. Further, assessments made by farmers on Microsoft’s Product Reaction Cards (MPRC) showed that the system was easy to use, reliable and efficient.

Keywords:

IoT, Automated irrigation, Sustainable farming, Smart irrigation system, Raspberry Pi.

References:

[1] FAO, “The Future of Food and Agriculture – Trends and Challenges,” Food and Agriculture Organization of the United Nations, Rome, 2017.
[Google Scholar] [Publisher Link]
[2] Joaquín Gutiérrez et al., "Automated Irrigation System Using a Wireless Sensor Network and GPRS Module," IEEE Transactions on Instrumentation and Measurement, vol. 63, no. 1, pp. 166-176, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Laura García et al., “IoT-Based Smart Irrigation Systems: An Overview on the Recent Trends on Sensors and IoT Systems for Irrigation in Precision Agriculture,” Sensors, vol. 20, no. 4, pp. 1-48, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Wei Li et al., "Review of Sensor Network-Based Irrigation Systems Using IoT and Remote Sensing,” Advances in Meteorology, vol. 2020, no. 1, pp. 1-14, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Francisco Puig, Juan Antonio Rodríguez Díaz, and María Auxiliadora Soriano, “Development of a Low-Cost Open-Source Platform for Smart Irrigation Systems,” Agronomy, vol. 12, no. 12, pp. 1-19, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[6] “Advance Information: FLEX ChipTM Signal Processor (MC68175/D),” Motorola, Freescale Semiconductor, 1996.
[Publisher Link]
[7] N. Ananthi et al., “IoT Based Smart Soil Monitoring System for Agricultural Production,” 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR), Chennai, India, pp. 209-214, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Jabar H. Yousif, and Khaled Abdalgader, “Experimental and Mathematical Models for Real-Time Monitoring and Auto Watering Using IoT Architecture,” Computers, vol. 11, no. 1, pp. 1-17, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Amarendra Goap et al., “An IoT Based Smart Irrigation Management System Using Machine Learning and Open Source Technologies,” Computers and Electronics in Agriculture, vol. 155, pp. 41-49, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[10] David Vallejo-Gómez, Marisol Osorio, and Carlos A. Hincapié, “Smart Irrigation Systems in Agriculture: A Systematic Review,” Agronomy, vol. 13, no. 2, pp. 1-25, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Achilles D. Boursianis et al., “Internet of Things (IoT) and Agricultural Unmanned Aerial Vehicles (UAVs) in Smart Farming: A Comprehensive Review,” Internet of Things, vol. 18, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Neha K. Nawandar, and Vishal R. Satpute, “IoT Based Low Cost and Intelligent Module for Smart Irrigation System,” Computers and Electronics in Agriculture, vol. 162, pp. 979-990, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[13] A.A. Raneesha Madushanki et al., “Adoption of the Internet of Things (IoT) in Agriculture and Smart Farming towards Urban Greening: A Review,” International Journal of Advanced Computer Science and Applications, vol. 10, no. 4, pp. 11-28, 2019.[Google Scholar] [Publisher Link]