article · Results in Engineering
A cloud-based smart irrigation system has been developed to link multiple small-scale farms and centralise agricultural data to optimise water management. Operating within a solar-powered real-world testbed, the platform collects, stores, and analyses big data to guide irrigation decisions, with a particular focus on arid environments facing water scarcity. The setup integrates weather prediction services to refine watering schedules during intermittent rainfall. Built using low-cost wireless sensor networks, embedded systems, an NI CompactRIO controller, and cloud computing, the smart farm prototype demonstrates measurable reductions in water consumption. Alongside the operational system, a structured deployment methodology provides an adaptable framework for implementing similar connected irrigation infrastructure in agricultural settings.
Agriculture faces severe pressures from climate change and freshwater shortages, particularly in arid areas. By combining solar energy, weather forecasting, and sensor networks, connected irrigation systems can drastically cut water waste while supporting crop production. Centralised cloud monitoring also allows multiple small-scale agricultural operations to coordinate and improve their resource management efficiently.
The system offers practical applications for smallholder agricultural operators and farm managers in arid, sun-rich regions seeking to lower water usage and energy costs. Utilising low-cost wireless sensors and an NI CompactRIO controller, the technology is at the applied prototype stage, having been validated in a functional, solar-powered testbed. Wider commercial rollout would require adapting the deployment methodology to varied local field conditions.
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It is widely acknowledged that traditional agricultural practices must effectively address the increasing global demand for food while facing water scarcity and climate change challenges. The imperative for environmentally sustainable agricultural approaches has never been more urgent. In response, IoT-based Smart Agriculture has emerged as a promising solution. Smart Agriculture can significantly bolster agricultural development by integrating renewable energy sources, particularly in arid regions with abundant sunlight. Real-time control systems utilizing big data acquisition and processing are pivotal in this advancement. This study introduces a cloud-based smart irrigation system to connect numerous small-scale smart farms and centralize pertinent data. The system optimizes irrigation water usage through comprehensive big data collection, storage, and analysis. Leveraging the insights from this data can facilitate informed decision-making regarding water management, thereby fostering conservation efforts, particularly in arid regions. Additionally, this research explores weather prediction services to enhance irrigation control, particularly during intermittent rainy periods, within a real-world testbed powered by solar energy. The testbed incorporates a sophisticated big data management system. It showcases a Smart Farm prototype leveraging the Internet of Things, embedded systems, low-cost Wireless Sensor Networks, NI CompactRIO controller, and Cloud Computing. Encouragingly, the results demonstrate tangible improvements in water conservation. Furthermore, the deployment methodology outlined in this study provides a clear roadmap that can be readily adapted for similar research endeavors. © 2023 Elsevier Inc. All rights reserved.
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DOI: 10.1016/j.rineng.2024.102283
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