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. 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. A new study by TSYS School computer scientist Mohamed Riduan Abid and his colleagues from Moulay Ismail University, Sidi Mohamed Ben Abdellah University, Al Akhawayn University, the Arava Institute for Environmental Studies, the University of Houston and Alfaisal University introduces a Cloud-based smart irrigation system to connect numerous small-scale smart farms and centralize pertinent data. Their system optimizes irrigation water usage through comprehensive big data collection, storage, and analysis. Their study, which appears in the current issue of Results in Engineering, argues that leveraging the insights from these data can facilitate informed decision-making regarding water management, thereby fostering conservation efforts, particularly in arid regions. Additionally, their study 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 that 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, while the deployment methodology outlined in their study provides a clear roadmap that can be readily adapted for similar research endeavors.
Comments
Post a Comment