Smart mobile learning system for pesticide management

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.

Authors

Publication Details

Journal
International Journal of Engineering in Computer Science
Published
2025-01-01
DOI
https://doi.org/10.33545/26633582.2025.v7.i1c.176
Primary Topic
Greenhouse Technology and Climate Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smart mobile learning system for pesticide management

Edward D. Joseph, Philip Nantok
International Journal of Engineering in Computer Science
Greenhouse Technology and Climate Control
article

Smart mobile learning system for pesticide management

Edward D. Joseph, Philip Nantok
article en

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.

International Journal of Engineering in Computer ScienceVol. 7(1)
Zero hunger
Openalex Percentile: Top 91%
Greenhouse Technology and Climate Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.