Optimizing Water Management in Agriculture: The Role of IoT-Powered Smart Irrigation Systems in Addressing Global Food Security and Water Scarcity
Mahdi Sabati Gavgani
研究物联网智能灌溉系统优化农业用水,提升粮食安全与缓解水资源短缺。
混合方法:案例定量分析与农户专家定性访谈,评估传感器、天气预报和自动灌溉技术。
智能灌溉节水30%,增产15-20%,实时数据分析优化灌溉调度。
可探索智能灌溉系统在不同作物、气候和农户采纳障碍下的适应性,以及政策激励对推广的影响。
论文实证智能灌溉节水30%增产20%,对农业水资源管理有参考价值,但时效性较低。
Objective: This study aims to explore the impact of IoT-powered smart irrigation systems on optimizing water management in agriculture, with a specific focus on addressing global food security and mitigating water scarcity challenges. Materials and Methods: The research employs a mixed-methods approach, combining quantitative data analysis from agricultural case studies and qualitative interviews with farmers and agricultural experts. The study assesses the effectiveness of smart irrigation technologies, including soil moisture sensors, weather forecasting tools, and automated irrigation systems, in improving water use efficiency and crop yields. Results and Discussion: The findings indicate that IoT-powered smart irrigation systems significantly enhance water management practices in agriculture. These systems result in a reduction of up to 30% in water usage, while simultaneously increasing crop productivity by 15-20%. Additionally, the integration of real-time data analytics allows for more precise irrigation scheduling, which contributes to sustainable agricultural practices and improved food security. Conclusions: This research contributes to the existing literature by providing empirical evidence of the benefits of IoT technologies in agriculture. It highlights the potential of smart irrigation systems as a viable solution to the dual challenges of food security and water scarcity. The findings emphasize the need for policy interventions and investment in technology to facilitate the adoption of these systems in farming practices worldwide.