The integration of artificial intelligence (AI) and the internet of things (IoT) with related to smart agriculture has changes in a new era of efficiency and sustainability in farming practices. This abstract provides an overview of AI-IoT-enabled smart agriculture and its importance in addressing modern agricultural challenges. In today's rapidly evolving agricultural landscape, smart agriculture, driven by AI and IoT technologies, has emerged as a transformative solution. This synergy combines AI's data processing and analytical capabilities with the real-time connectivity of IoT devices to create a dynamic and data-driven agricultural ecosystem. The convergence of AI and IoT in agriculture not only empowers farmers with real-time information but also helps meet the growing demand for food in a more sustainable and environmentally responsible manner. However, as technology continues to evolve, challenges related to data security, interoperability, and accessibility need to be addressed to ensure the widespread adoption of smart agriculture practices.
TopIntroduction To Ai – Iot Based Environment, Smart Agriculture
In recent years, the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) has revolutionized various industries, and agriculture is no exception. Smart agriculture, also known as precision agriculture, uses AI and IoT technologies to make farming more efficient, sustainable, and productive (Akkaş M. A. et al., 2017). This approach combines data-driven decision-making with real-time monitoring and automation to optimize various aspects of agricultural operations (refer figure 1).
Figure 1. Components of AI-IoT-Based Smart Agriculture
Benefits of AI-IoT-Based Smart Agriculture as Increased Efficiency (AI-driven information help optimize resource utilization, reduce waste, and increase crop yields., Sustainability (i.e., By minimizing water and pesticide use and promoting responsible farming practices, smart agriculture contributes to environmental sustainability), Improved Crop Quality (i.e., AI can help identify and address issues early, leading to higher-quality crops and reduced losses), Remote Monitoring (i.e., Farmers can monitor and manage their farms remotely, reducing the need for physical presence on-site), Data-Driven Decision-Making (i.e., AI-powered recommendations based on real-time data enhance decision-making and increase the chances of success).
In summary, AI-IoT-based smart agriculture is a transformative approach that holds the potential to address global food security challenges, reduce environmental impact, and increase agricultural productivity. As technology continues to advance, the adoption of these systems in agriculture is likely to grow, benefitting both farmers and the environment.
TopChallenges In Traditional Agriculture
Traditional agriculture faces several challenges that can hinder its productivity, sustainability, and the livelihoods of those engaged in farming (Ananthi N. et al., 2017; Anastasi G. et al., 2009). Some of the key challenges in traditional agriculture include: