Titlebook: Artificial Intelligence Techniques in Smart Agriculture; Siddharth Singh Chouhan,Akash Saxena,Sanjeev Jain Book 2024 The Editor(s) (if app

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Assessing the Importance and Need of Artificial Intelligence for Precision Agriculture,logy have directed the future of almost every industry towards this domain. This technology has helped to automate a number of process and applications. Adopting intelligence upsurges the quality and quantity of the products. It enhances the workers skill and simulates the problem-solving mechanism

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Challenges in Achieving Artificial Intelligence in Agriculture,Collaboratively addressing the numerous sophisticated technical and social issues is necessary for fully utilizing the potential of AI for small-scale farmers who are at risk. The primary issue that has been highlighted is the lack of high-quality data that represent different farm types, marginaliz

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Introduction to Artificial Intelligence Techniques in Agricultural Applications and Their Future Aszed agriculture, increasing efficiency, productivity, and sustainability. One of the main drivers of this change is the integration of artificial intelligence (AI) technologies encompassing machine learning (ML), computer vision and data analytics into agriculture. AI has become a revolutionary tool

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Smart Farming Management System: Pre and Post-Production Interventions,rming practices. The necessity of smart farming in addressing global challenges such as increasing food demand, resource scarcity, and the impacts of climate change has been highlighted. Smart farming, driven by technologies like precision agriculture, digital farming, artificial intelligence (AI),

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Deep Learning-Based Plant Stress Diagnosis: An Optimized Generative Augmentation Model Approach,icultural business has a number of barriers, notably changing weather conditions that induce a variety of serious diseases in plants, depressing crop yields, and revenues. An optimized Convolution Neural Network model for identifying and reliably detecting plant stress phenotyping. By using the capa

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Transformative Impact of AI-Driven Computer Vision in Agriculture, computer vision. This chapter explores the profound impact of AI-driven computer vision, highlighting its crucial role in changing how we manage crops, detect diseases, and optimize resources in agriculture. This integration goes beyond just improving precision farming; it empowers effective crop m

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