Titlebook: Computational Intelligence in Internet of Agricultural Things; M. G. Sumithra,Malathy Sathyamoorthy,Mariya Ouaiss Book 2024 The Editor(s)

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Advancing Plant Disease Detection with Hybrid Models: Vision Transformer and CNN-Based Approaches,farming. Plant disease detection extends its significance beyond the boundaries of agriculture, with far-reaching implications. It contributes to economic stability, sustainable farming practices, reduced pesticide usage, product quality assurance, global trade compliance, climate resilience, and th

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Innovating with Quantum Computing Approaches in Block-Chain for Enhanced Security and Data Privacy n technology. The security of data collected in large scale by IoT devices in agriculture is the primary issue in the stage of implementation. One of the main objectives of this research is to leverage the power of quantum computing in improving the security infrastructure of blockchain, which is an

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Implementing Fog Computing in Precision Agriculture for Real-Time Soil Health Monitoring and Data Malth and the management of agricultural data possible. The contemporary industrial agriculture face the challenge of the evaluation of the soil condition appropriately and on time if one aims to improve the production of crops and resource efficiency. The core goal of the mission is to leverage the

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Artificial Intelligence in Agriculture: Potential Applications and Future Aspects,ion. An overview of AI‘s use in agronomic fields and its advancements in lab research are given in this chapter. The chapter begins by outlining two areas in which artificial intelligence (AI) may be particularly useful: soil management and farm management. Next, the technology known as the Internet

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Case Study on Smart Irrigation Using Internet of Things and XAI Techniques,lobal warming and greenhouse gases. The photovoltaic (PV) system employs solar energy, which is a form of renewable energy is environmentally friendly and sustainable; however, it is challenging to generate power with this technology. The best solution to this issue is to use efficient algorithms th

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1860-949X AI techniques to generate a greater data-driven solution fo.This book focuses on the integration of IoT and AI techniques to generate greater data-driven solutions for the agriculture industry. It also focuses on computational intelligence (CI), machine learning, and AI techniques along with curren

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