Analysis of IoT-Based Smart Pest Control Systems for Farms in Birnin Kebbi LGA, Kebbi State
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Background of the study:
Effective pest control is vital for maximizing crop yields and ensuring food security, yet traditional methods often rely on manual monitoring and reactive interventions that are inefficient and environmentally unsustainable. In Birnin Kebbi LGA, Kebbi State, farmers face significant challenges in controlling pest outbreaks that can decimate crops. The integration of IoT technology into pest control systems offers a promising solution by automating the detection and management of pests. Smart pest control systems employ sensors to monitor environmental conditions, pest activity, and crop health in real time (Ibrahim, 2023). Data collected by these sensors are transmitted wirelessly to centralized platforms where advanced analytics, including machine learning algorithms, can detect early signs of infestations and predict their spread (Adeniyi, 2024). This proactive approach enables farmers to apply targeted interventions, such as precise pesticide application or biological control measures, thereby reducing overall chemical use and minimizing environmental impact. Additionally, the system provides continuous feedback, allowing for the adjustment of control strategies based on real-time field conditions. By optimizing pest control methods, these IoT-based solutions improve crop health and yield, reduce operational costs, and contribute to sustainable agricultural practices (Udo, 2025). The technology also supports integrated pest management (IPM) strategies by combining real-time monitoring with historical data analysis, enabling a more efficient and environmentally friendly approach to pest control.
Statement of the problem:
Farmers in Birnin Kebbi LGA face recurring losses due to pest infestations, as traditional pest control methods are largely manual and reactive, often leading to delayed responses and overuse of chemical pesticides (Ibrahim, 2023). The absence of continuous, real-time monitoring means that pest outbreaks are typically detected only after significant crop damage has occurred, resulting in reduced yields and increased production costs. Manual scouting is labor-intensive, inconsistent, and unable to capture the rapid changes in pest populations, which compromises the effectiveness of intervention measures. Furthermore, the excessive use of pesticides not only raises production costs but also poses environmental and health risks. Financial constraints and limited access to advanced technologies further exacerbate these challenges, leaving farmers with inadequate tools to manage pest threats efficiently (Adeniyi, 2024). Without a smart, IoT-based pest control system, the agricultural sector remains vulnerable to large-scale infestations that jeopardize food security and farmer livelihoods. Implementing a proactive, data-driven solution is critical for early pest detection, precise intervention, and sustainable pest management practices (Udo, 2025).
Objectives of the study:
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To design an IoT-based smart pest control system for continuous monitoring of pest activity.
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To evaluate the system’s effectiveness in reducing pest-related crop losses.
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To propose strategies for integrating the system with existing farm management practices.
Research questions:
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How effective is the IoT-based system in detecting early signs of pest infestations in real time?
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What improvements in crop yield and pesticide usage can be observed after implementation?
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How can the system be integrated with current agricultural practices to optimize pest control?
Significance of the study:
This study is significant as it offers a sustainable, technology-driven solution to enhance pest control in agriculture. By enabling early detection and targeted intervention, the IoT-based system reduces crop losses, lowers chemical usage, and promotes sustainable farming practices in Birnin Kebbi LGA, thereby contributing to food security and environmental health.
Scope and limitations of the study:
This study is limited to the analysis and evaluation of IoT-based smart pest control systems for farms in Birnin Kebbi LGA, Kebbi State. It does not extend to other agricultural regions or different pest management technologies.
Definitions of terms:
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IoT (Internet of Things): A network of devices that collect and exchange real-time data.
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Pest Control System: A system designed to monitor and manage pest populations.
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Integrated Pest Management (IPM): A sustainable approach combining biological, cultural, and chemical methods for pest control.
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