Food is a fundamental necessity for human survival, leading to the expansion of crop cultivation beyond traditional rural areas into urban environments. Urban farming presents several advantages, including access to fresh, organic produce and the creation of new job opportunities. However, despite these benefits, urban agriculture faces notable challenges. Organic foods are often more expensive, and the success of urban farming initiatives can be hampered by insufficient space for plant growth, insufficient knowledge, inadequate conditions for plant growth, and significant environmental changes driven by global development.
To address these challenges, this research focuses on leveraging Artificial Intelligence (AI) techniques to enhance urban farming practices. By applying AI, it is possible to optimize growing conditions, predict and manage plant needs, and adapt to changing environmental factors. AI can also help streamline operations and reduce costs, making urban farming more viable and effective. This approach aims to improve food security by making urban agriculture more efficient and sustainable, thus contributing to a more resilient food system capable of meeting the demands of a growing population.
The above framework represents a comprehensive overview of the components, connectivity, and operations behind the AI model.
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