پیشرفت آبیاری قطره ای زیرسطحی با رایانه های شخصی بازیافتی به عنوان کنترل کننده های هوشمند همراه با برداشت موثر آب باران
پذیرفته شده برای ارائه شفاهی
کد مقاله : 1087-SCWMCCAN
نویسندگان
1Graduated from the University of Portsmouth, School of Computing, Portsmouth UK
European Engineer (EUR ING) from Engineers Europe (formerly FEANI)
22Professor, Kurdistan Agricultural and Natural Resources Research and Education Center, REEO, Sanandaj, Iran.
چکیده
کمبود آب یک مسئله حیاتی در مناطق خشکی مانند ایران است، جایی که کشاورزی به شدت به آبیاری متکی است. در این مطالعه، ما یک رویکرد جدید برای مدیریت آب با ترکیب آبیاری قطره‌ای زیرسطحی با رایانه‌های شخصی بازیافتی به عنوان کنترل‌کننده‌های هوشمند و برداشت موثر آب باران پیشنهاد می‌کنیم. با استفاده از فناوری هوش مصنوعی، این کنترل‌کننده‌های هوشمند می‌توانند مصرف آب را بر اساس داده‌های زمان واقعی بهینه کنند و به شیوه‌های آبیاری کارآمدتر منجر شوند. علاوه بر این، سیستم های جمع آوری آب باران می تواند آب آبیاری را تکمیل کند و اتکا به منابع آب سنتی را کاهش دهد. اثربخشی این تحقیق از طریق یک آزمایش میدانی برای ارزیابی تأثیر آن بر عملکرد محصول و مصرف آب مورد ارزیابی قرار خواهد گرفت. این رویکرد یکپارچه پتانسیل بهبود بهره وری آب در کشاورزی، به ویژه در مناطقی که با کمبود آب مواجه هستند را دارد. این تحقیق به پیشرفت شیوه‌های کشاورزی هوشمند و مدیریت پایدار آب و استراتژی‌های امنیت غذایی کمک می‌کند.
Water scarcity is a critical issue in arid regions such as Iran, where agriculture heavily relies on irrigation. In this study, we propose a novel approach to water management by combining subsurface drip irrigation with recycled PCs as smart controllers and effective rainwater harvesting. By utilizing AI technology, these smart controllers can optimize water usage based on real-time data, leading to more efficient irrigation practices. Additionally, rainwater harvesting systems can supplement irrigation water, reducing reliance on traditional water sources.
Water scarcity is a critical issue in arid regions such as Iran, where agriculture heavily relies on irrigation. In this study, we propose a novel approach to water management by combining subsurface drip irrigation with recycled PCs as smart controllers and effective rainwater harvesting. By utilizing AI technology, these smart controllers can optimize water usage based on real-time data, leading to more efficient irrigation practices. Additionally, rainwater harvesting systems can supplement irrigation water, reducing reliance on traditional water sources.
کلیدواژه ها
Title
Advancing Subsurface Drip Irrigation with recycled PC’s as smart controllers combined with effective rainwater harvesting
Authors
Babak Yeganegy-Bruckhoff, Ata Amini
Abstract
Water scarcity is a critical issue in arid regions such as Iran, where agriculture heavily relies on irrigation. In this study, we propose a novel approach to water management by combining subsurface drip irrigation with recycled PCs as smart controllers and effective rainwater harvesting. By utilizing AI technology, these smart controllers can optimize water usage based on real-time data, leading to more efficient irrigation practices. Additionally, rainwater harvesting systems can supplement irrigation water, reducing reliance on traditional water sources. The effectiveness of the research will be evaluated through a field trial assessing its impact on crop yield and water consumption. This integrated approach has the potential to improve water efficiency in agriculture, particularly in regions facing water scarcity. This research contributes to the advancement of smart farming practices and sustainable water management and food security strategies. Water scarcity is a critical issue in arid regions such as Iran, where agriculture heavily relies on irrigation. In this study, we propose a novel approach to water management by combining subsurface drip irrigation with recycled PCs as smart controllers and effective rainwater harvesting. By utilizing AI technology, these smart controllers can optimize water usage based on real-time data, leading to more efficient irrigation practices. Additionally, rainwater harvesting systems can supplement irrigation water, reducing reliance on traditional water sources.
Keywords
Rainwater Harvesting, AI, Smart Farming, Computer upcycling, irrigation system