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International Journal of Engineering in Computer Science

Impact Factor (RJIF): 10.52, P-ISSN: 2663-3582, E-ISSN: 2663-3590
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2025, Vol. 7, Issue 1, Part C

Smart mobile learning system for pesticide management


Author(s): Philip Nantok and Eseyin Joseph

Abstract: Pesticide management is a crucial aspect of agricultural sustainability and environmental safety. However, the lack of proper training and accessibility to real-time information has led to misuse, causing health and ecological hazards. This study proposes a Smart Mobile Learning System (SMLS) for pesticide management, leveraging mobile technologies to educate farmers, agricultural workers, and policymakers. The system integrates Artificial Intelligence (AI), Internet of Things (IoT), and cloud computing to deliver real-time recommendations, dosage calculations, and safety guidelines. A prototype system was developed and evaluated based on usability, effectiveness, and user satisfaction. Findings show that 90% of users improved their pesticide application accuracy and safety adherence. The study concludes that a mobile-based learning system enhances pesticide management, reducing health risks and improving sustainability.

DOI: https://www.doi.org/10.33545/26633582.2025.v7.i1c.176

Pages: 193-194 | Views: 958 | Downloads: 529

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International Journal of Engineering in Computer Science
How to cite this article:
Philip Nantok, Eseyin Joseph. Smart mobile learning system for pesticide management. Int J Eng Comput Sci 2025;7(1):193-194. DOI: 10.33545/26633582.2025.v7.i1c.176
International Journal of Engineering in Computer Science

International Journal of Engineering in Computer Science

International Journal of Engineering in Computer Science
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