Recent advances in insect pest management strategies emphasizing on Artificial intelligence: A overview
Article Main
Abstract
Insect pests pose a serious threat to agricultural production and food security, accounting for 30–40% of yearly crop losses worldwide. Conventional pest control techniques are often labour-intensive, ineffective, and unable to adapt to the changing habits of pests. By enhancing pest identification, classification, and management through the application of sophisticated algorithms, sensor technologies, and predictive modelling, Artificial intelligence (AI) provides a game-changing solution. AI-powered methods minimize financial losses and promote sustainable agriculture by enabling early pest detection, reducing pesticide overuse, and facilitating data-driven decision-making. This paper provides a comprehensive examination of AI and smart sensor applications in pest management, highlighting their contributions to crop monitoring, environmental assessment, and resource efficiency. Weather monitoring systems, crop health sensors, automatic irrigation controllers, and soil sensors are some of the key technologies covered. Furthermore, the potential of innovations such as sensor fusion, hyperspectral imaging, and drone-based sensing to enhance real-time agricultural data collection and decision-making is investigated. It also examines how the Internet of Things (IoT) and AI-driven analytics might be integrated into precision agriculture to maximize pest control, fertilization, and irrigation. AI and smart sensors support sustainable pest management and robust agricultural ecosystems by facilitating effective resource use and reducing environmental impact. This review emphasizes how important AI and smart sensor technologies are to improving precision farming and bolstering global food security.
Article Details
Article Details
Keywords
Artificial Intelligence (AI), Integrated pest management, Nanopesticide, Weak AI precision farming
References
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Recent advances in insect pest management strategies emphasizing on Artificial intelligence: A overview. (2025). Journal of Applied and Natural Science, 17(3), 1409-1419. https://doi.org/10.31018/jans.v17i3.6710
