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<p>The growing demand for nutritionally rich food, driven by population growth, climate change, and greater awareness of diet-related health. This situation requires a shift in traditional agriculture, which was focused on yield rather than nutritional quality. Furthermore, the global food system is facing mounting burden from climate change, soil degradation, and supply chain disruptions. Therefore, this systematic review examines how emerging technologies, especially artificial intelligence (AI) and the Internet of Things (IoT), can transform traditional farming techniques into nutrition-focused farming to meet global demands. Research and review papers on AI and IoT implementation were retrieved from Google Scholar, IEEE Explore, ScienceDirect, Springer, PubMed, Scopus and Taylor &amp; Francis databases published between 2017 and 2025. We first examined the global market trends of AI and IoT-enabled technologies in the agriculture sector and then their implementation in agriculture parameter tracking, disease and pest forecasting, real-time monitoring of nutrients, biofortification, early warning systems for nutritional disruptions, and nutritional advisory for farmers. This systematic review highlights the importance of AI and IoT integration in automation, intelligent sensors and data-driven tools to foster sustainable farming, optimise resource utilisation, and scalability, leading to nutrition-sensitive agri-food. The adoption of AI and IoT is not merely a technological advancement but a pathway toward improving food quality while ensuring nutrition security and achieving sustainable agricultural goals (SDG 2, SDG 3 and SDG 9). The key challenges, including data privacy, limited digital access, and farmer adoption gaps, especially in developing countries, identified in this review, can be improved with good governance policies and research recommendations. The integration of advanced digital technologies with sustainable farming practices can render a solution for global challenges such as climate change, declining soil fertility, malnutrition, and food insecurity. Furthermore, this review provides directions for future research to develop nutrition-focused, resilient, and sustainable agricultural systems.</p>

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Ai and IoT are no longer limited to high-tech labs but are improving nutrition-focused agricultural farming

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月7日

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  • Madhav Dhakal,
  • Minali Banerjee,
  • Krishna Kant Pandey,
  • Chandrabhan Seniya

摘要

The growing demand for nutritionally rich food, driven by population growth, climate change, and greater awareness of diet-related health. This situation requires a shift in traditional agriculture, which was focused on yield rather than nutritional quality. Furthermore, the global food system is facing mounting burden from climate change, soil degradation, and supply chain disruptions. Therefore, this systematic review examines how emerging technologies, especially artificial intelligence (AI) and the Internet of Things (IoT), can transform traditional farming techniques into nutrition-focused farming to meet global demands. Research and review papers on AI and IoT implementation were retrieved from Google Scholar, IEEE Explore, ScienceDirect, Springer, PubMed, Scopus and Taylor & Francis databases published between 2017 and 2025. We first examined the global market trends of AI and IoT-enabled technologies in the agriculture sector and then their implementation in agriculture parameter tracking, disease and pest forecasting, real-time monitoring of nutrients, biofortification, early warning systems for nutritional disruptions, and nutritional advisory for farmers. This systematic review highlights the importance of AI and IoT integration in automation, intelligent sensors and data-driven tools to foster sustainable farming, optimise resource utilisation, and scalability, leading to nutrition-sensitive agri-food. The adoption of AI and IoT is not merely a technological advancement but a pathway toward improving food quality while ensuring nutrition security and achieving sustainable agricultural goals (SDG 2, SDG 3 and SDG 9). The key challenges, including data privacy, limited digital access, and farmer adoption gaps, especially in developing countries, identified in this review, can be improved with good governance policies and research recommendations. The integration of advanced digital technologies with sustainable farming practices can render a solution for global challenges such as climate change, declining soil fertility, malnutrition, and food insecurity. Furthermore, this review provides directions for future research to develop nutrition-focused, resilient, and sustainable agricultural systems.